Technology as an Enabler to Entrepreneurial Performance: Evidence from Past Literature of Quantitative Research

Technology as an Enabler to Entrepreneurial Performance: Evidence from Past Literature of Quantitative Research | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Systematic Review Technology as an Enabler to Entrepreneurial Performance: Evidence from Past Literature of Quantitative Research Raunak Gupta, Anuja Sharma This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8631639/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Entrepreneurial performance is a well-known concept in the domain of entrepreneurship. While the previous research in this area has linked entrepreneurial performance to a number of factors, including personality traits, entrepreneurial orientation, firm strategy, networking ability, and many more, recent literature has drawn significant attention to the impact of technology adoption, innovation capability, and related variables on the performance of entrepreneurial ventures. Therefore, we conducted a systematic literature review employing the bibliometric methodology to identify the key research areas and directions of earlier quantitative research linking technology and entrepreneurial performance. The research findings indicate that it is not always that technology adoption will lead to better firm performance. Therefore, it also emphasizes the importance of identifying the required characteristics of the firms and supporting actors and determining the optimal timing for technology adoption, which may lead to better firm performance. The findings also revealed the major theories, methodologies used, and regions studied in this domain area of research since 1977. Entrepreneurship Management bibliometric analysis entrepreneurial performance innovation literature review technology Figures Figure 1 Figure 2 Introduction Entrepreneurs are believed to be creative, innovative, and risk-takers in their approach to driving growth for their entrepreneurial ventures (Zhao, Seibert and Lumpkin, 2010 ; Laguía, Moriano and Gorgievski, 2019 ; Falahat, Soto-Acosta and Ramayah, 2022 ). While the last few years have witnessed rapid growth and advancements in technology, it has also put a great emphasis on entrepreneurs utilizing these technological innovations in their entrepreneurial ventures (Makridakis, 2017 ). This has resulted in an increase in studies focusing on the impact of constructs related to technology, artificial intelligence, and innovation on entrepreneurial performance (Chatterjee, Dutta Gupta and Upadhyay, 2020 ; Fang et al., 2022 ; Tran and Murphy, 2023 ). The concept of entrepreneurial performance is a widely recognized concept in the literature of entrepreneurship. Measuring entrepreneurial performance shows how effectively entrepreneurs' efforts and the ecosystem's support to entrepreneurs are getting paid off because entrepreneurship is considered to be a driver of employment generation and bringing socio-economic prosperity to economies. Entrepreneurial performance measures the performance of an entrepreneurial venture using several parameters comprising financial and non-financial characteristics (Díaz-Pichardo, Juárez-Luis and Sánchez-Medina, 2014 ). Whereas prior research in the area of measuring entrepreneurial performance has linked it to several factors like personality traits, entrepreneurial orientation, firm strategy, networking ability, and many others (Zhao, Seibert and Lumpkin, 2010 ; Lechner and Gudmundsson, 2014 ; Karami and Tang, 2019 ; Fang et al., 2022 ), recent literature has also shown significant interest in understanding the impact of technology adoption, innovation capability, and related variables on the performance of entrepreneurial ventures in order to understand better what drives the entrepreneurial performance. This research study attempts to synthesize the published empirical literature linking technology to entrepreneurial performance and perform a systematic review to identify common themes, constructs, theoretical foundations, and future directions for the research. Reviews play a crucial role in the progression of a research area through summarization of the published literature in that specified area and bringing noble insights for future research (Bland, Meurer and Maldonado, 1995 ). While earlier attempts to synthesize, summarize, and connect the research on entrepreneurial performance have explored it from the perspectives of its relationship with personality, entrepreneurial intentions, entrepreneurial learning, and human capital interventions (Zhao, Seibert and Lumpkin, 2010 ; Tseng, 2013 ), the authors have not come across research that has performed a systematic review for the link between technology and entrepreneurial performance using bibliometric analysis, especially in the context of researches that have utilised quantitative methods. The importance of entrepreneurial performance as a fundamental concept in the entrepreneurship literature and its association with technology encourages us to explore it from the perspective of its relationship with technology interventions (Kwun and Jeong, 2012 ; Poudel, Carter and Lonial, 2019 ). Using a systematic methodology, we aim to recognize the key research areas and directions of earlier quantitative research linking technology and entrepreneurial performance rather than to offer a full interpretation. In conclusion, the current study aims to summarize the diverse quantitative studies connecting technology and entrepreneurial performance. We offer insights into theoretically significant topics that have gained attention in the literature through statistical methods by concentrating solely on studies evaluating hypothesized correlations. Research Design/Methodology/Approach To perform the systematic review of the empirical studies linking technology and entrepreneurial performance, we adopted the PRISMA framework (Liberati et al. , 2009), which advocates the four steps: Identification, Screening, Eligibility, and Inclusion for systematically sampling the articles for review. During the first step, i.e., Identification, a comprehensive literature search was performed using the Scopus database to sample the relevant research studies linking technology and entrepreneurial performance. The search string used while searching the database was: ("entrepre* performance" OR "firm performance" OR "SME performance" OR "enterprise performance" OR "venture performance") AND ("Technology" OR "Innovation" OR "AI" OR "Artificial Intelligence"). While the term entrepre* was used to capture all the possible variations like entrepreneur, entrepreneurial, entrepreneurship, etc., we have also used similar keywords like firm, SME, enterprise, and venture performance to capture all possible research studies relevant to entrepreneurial performance. Further, we have only used keywords like Technology, Innovation, and Artificial Intelligence to limit our focus to the broader terms used in the research in reference to technology. The search results were restricted to journal articles and the English language in order to sample only high-quality and widely applicable research studies (Miller and Serzan, 1984). The bibliometric data for these sampled research studies was exported in four phases [1] , categorized by the timelines in which research studies were published. As a result, a total list of 4631 research studies (123 up to 1999, 653 during 2000 – 2010, 1070 during 2011 – 2016, 1221 during 2017 – 2020, and 1564 during 2021 – 2023) was exported. During the screening phase, the first criterion was applied to filter out the research studies that were not published in the ABDC-rated journals because the research studies published in the ABDC-rated journals are considered to be of high impact in the field of social science and are more comprehensive than any other journal ranking list (Mura and Pahlevan Sharif, 2015). The second criterion was applied to filter out the research studies which were not primarily empirical. To apply this criterion, we checked the abstracts of these research studies to verify the occurrence of one out of seven procedural keywords (‘data’, ‘test’, ‘statistical’, ‘empirical’, ‘result’, ‘finding’, and ‘evidence’) as used by (Wales, Gupta and Mousa, 2013). The third filter was applied to eliminate all those research studies that have not received any citations to date. However, an exemption was made for the research studies published in 2023 while applying this criterion, as these were the most recent studies, and the chances for them to get cited were very low. After applying all three criteria during the screening phase, we were left with a total list of 2731 research studies (70 up to 1999, 483 during 2000 – 2010, 699 during 2011 – 2016, 670 during 2017 – 2020, and 809 during 2021 – 2023). To further verify the eligibility of these 2731 research studies for inclusion in the list of research studies for this literature review, we went through the abstracts for all the remaining studies carefully to eliminate all those research studies that were not directly linked with the impact of technology interventions on entrepreneurial performance and empirical content having mention of statistical analysis. For example, we eliminated the studies focusing on the role of venture capitalists in high-technology firms, the role of crime in the innovation potential of firms, the relationship between HR policies and practices with firm performance, meta-analytical methodologies to review the literature on innovation and organizational performance, and likewise. We have also eliminated studies that have not utilized any statistical method to analyze the data collected, as evidenced by their abstracts. After verifying the eligibility during this phase, we were left with 1531 research studies (38 up to 1999, 304 during 2000 – 2010, 383 during 2011 – 2016, 345 during 2017 – 2020, and 461 during 2021 – 2023). These 1531 research studies were then included in this study to review them through bibliometric analysis using an R-based bibliometrix tool (Aria and Cuccurullo, 2017) and content analysis to uncover the diversity of aspects covered through the empirical studies linking technology and entrepreneurial performance and present the findings for further discussion and future agenda. Findings from Bibliometric Analysis Findings from Bibliometric Analysis Performance Analysis Performance analysis in a bibliometric analysis technique is similar to profiling participants in empirical studies, although it is conducted more rigorously by employing bibliometric metrics (Donthu et al. , 2021). A performance analysis is carried out in this study to uncover the following: (1) the trends in publication, (2) the most impactful research studies, (3) the top journals, (4) authors, (5) institutions, and (6) countries that have contributed significantly to the domain of this study. In fundamental analysis, a total of 1531 research studies were published in 396 journals by 3507 authors emphasizing the role of technology in enabling entrepreneurial performance since 1977. Only 127 research studies taken in this study were authored by a single author, which reflects that most of the research in this domain has been done collaboratively. 33.9% international co-authorship represents a significant proportion of the research done through cross-country collaboration. Figure 1 represents the research studies published yearly in different ratings journals per their ABDC ratings. Most of the research studies (894 research studies) taken into this study had been published in A* and A category journals. While looking at the yearly trends reveals that technology has always been a critical aspect of determining firm performance and has also been studied well in the literature on entrepreneurship since 1977, the interest of scholars in studying the link between technology and entrepreneurial performance has grown exponentially in recent times as more than 50% of the research studies, taken into this study, are published after 2016. It shows that the growing inclination of industries towards adopting the internet and digital-driven technologies like big data, cloud computing, IoT, etc., has resulted in increasing interest by scholars and researchers worldwide in studying their impact on firm performance. Since the data in this study had been collected in a phase-wise manner based on the time duration of studies published through the Scopus database, we have analyzed the remaining performance parameters like most impactful research studies, journals, authors, institutions, and countries that had contributed significantly to the domain area of this study, in the same phase-wise manner. Tables 1 – 5 show these performance metrics for this study. Table 1: Top 5 research studies during various time durations based on total citations Research Study Total Citations TC per Year 1977 - 1999 Powell TC, 1997, Strategic Manage J 1492 55.26 Bharadwaj AS, 1999, Manage Sci 809 32.36 Weill P, 1992, Inf Syst Res 646 20.19 Zahra SA, 1993, Strategic Manage J 527 17 Hill CWL, 1988, Strategic Manage J 490 13.61 2000 - 2010 Bharadwaj AS, 2000, MIS Quart Manage Inf Syst 3327 138.63 Rai A, 2006, MIS Quart Manage Inf Syst 1389 77.17 Christmann P, 2000, Acad Manage J 1354 56.42 Lee C, 2001, Strategic Manage J 1282 55.74 Stuart TE, 2000, Strategic Manage J 1247 51.96 2011 - 2016 Gunday G, 2011, Int J Prod Econ 896 68.92 Tallon PP, 2011, MIS Quart Manage Inf Syst 773 59.46 Akter S, 2016, Int J Prod Econ 726 90.75 Wang Z, 2012, Expert Sys Appl 648 54 Mithas S, 2011, MIS Quart Manage Inf Syst 635 48.85 2017 - 2020 Wamba SF, 2017, J Bus Res 1075 153.57 Rajapathirana RPJ, 2018, J Innov Knowl 411 68.5 Cai W, 2018, J Clean Prod 355 59.17 Tang M, 2018, Bus Strategy Environ 333 55.5 Ben Arfi W, 2018, Technol Forecast Soc Change 277 46.17 2021 - 2023 Mikalef P, 2021, Inf Manage 202 67.33 Tajvidi R, 2021, Comput Hum Behav 139 46.33 Gu M, 2021, Int J Prod Econ 129 43 Singh SK, 2022, Bus Strategy Environ 127 63.5 Clauss T, 2021, IEEE Trans Eng Manage 118 39.33 Looking at these metrics, it is evident from Table 1 that a maximum of the top-cited research studies in this domain area of study had been published in Strategic Management Journal (5038 total citations) and MIS Quarterly (6124 total citations). The summarized insights from these top-cited research studies is shared in brief in discussion section. Journal of Business Research (56 publications), Technology Analysis and Strategic Management (36 publications), Journal of Cleaner Production (19 publications), and Strategic Management Journal (16 publications) are some of the leading journals contributing the maximum number of research studies (see Table 2) to this domain area of study. Looking at the top authors (see Table 3) through their h_index and the total number of citations during each phase of the study, Bharadwaj AS (4136 total citations) is the only author who received the maximum number of citations combining all phases. Table 2: Top 5 journals during various time durations based on number of publications Name of the Journal Total Citations Number of Publications 1977 - 1999 Strategic Management Journal 2976 5 Journal of Business Venturing 1032 4 Economics of Innovation and New Technology 58 2 Information and Management 386 2 Information Systems Research 1087 2 2000 - 2010 Strategic Management Journal 6424 11 Journal of Management Information Systems 2875 10 Research Policy 2272 10 Information and Management 776 9 International Journal of Technology Management 271 9 2011 - 2016 Journal of Business Research 2841 19 Industrial Management and Data Systems 692 11 Management Decision 681 11 Technology Analysis and Strategic Management 331 10 Journal of Product Innovation Management 755 9 2017 - 2020 Journal of Business Research 2374 17 Technology Analysis and Strategic Management 360 12 Journal of Cleaner Production 1550 10 Technological Forecasting and Social Change 997 10 International Journal of Production Economics 634 9 2021 - 2023 Journal of Business Research 381 20 IEEE Transactions on Engineering Management 383 19 Technology Analysis and Strategic Management 124 14 Business Strategy and the Environment 382 7 Journal of Cleaner Production 231 9 Table 3: Top 5 authors during various time durations based on their h_index and Total Citation Name of the Author h_index Name of the Author Total Citation 1977 - 1999 Covin JG 2 Dent-Micallef A 1492 Zahra SA 2 Powell TC 1492 Alpar P 1 Zahra SA 813 Appiah-Adu K 1 Bharadwaj AS 809 Bartelsman E 1 Bharadwaj SG 809 2000 - 2010 Byrd TA 5 Bharadwaj AS 3327 Kraemer KL 5 Zhu K 2125 Tsai K-H 4 Kraemer KL 1749 Zhu K 4 Rai A 1523 Cavusgil ST 3 Patnayakuni R 1389 2011 - 2016 Sambamurthy V 5 Sambamurthy V 1297 Lee J-N 4 Mithas S 1258 Mithas S 4 Alpkan L 896 Calantone RJ 3 Gunday G 896 Cucculelli M 3 Kilic K 896 2017 - 2020 Anning-Dorson T 7 Akter S 1238 Bao Y 6 Childe SJ 1075 Wang Y 5 Dubey R 1075 Akter S 4 Gunasekaran A 1075 Fosso Wamba S 4 Ren SJ-F 1075 2021 - 2023 Chatterjee S 4 Mikalef P 203 Chaudhuri R 4 Gupta M 202 Chen Y 4 Chen Y 180 Kumar S 4 Del Giudice M 173 Wei Z 4 Singh SK 173 The authors affiliated with Michigan State University, USA (25 publications) have contributed the maximum number of research studies (see Table 4) to the domain area of this study. In terms of countries (see Table 5), the authors from the USA (192 publications), China (310 publications), Spain (98 publications), the United Kingdom (35 publications), and Australia (31 publications) have contributed to the maximum number of research studies, the contribution of Indian authors (27 publications during 2021 – 2023) to the domain area of this study has also started increasing in recent times. Table 4: Top 5 institutions during various time durations based on number of publications Name of the Institution Number of Publications 1977 - 1999 Auburn University 2 Ben-Gurion University of The Negev 1 Hebrew University of Jerusalem 1 STT. Univ. of New York at Buffalo 1 Seattle 1 2000 - 2010 Michigan State University 12 National Cheng Kung University 9 National Chung Cheng University 8 University of California 8 University of Tehran 8 2011 - 2016 Michigan State University 13 National Taiwan University 8 Griffith University 7 Lappeenranta University of Technology 7 National Chengchi University 7 2017 - 2020 University of Ghana Business School 13 University of Science and Technology of China 12 University of Murcia 11 Huazhong University of Science and Technology 9 Northwestern Polytechnical University 8 2021 - 2023 Jiangsu University 17 Central South University 10 Sichuan Agricultural University 10 Ural Federal University 10 Xi'an Jiaotong University 10 Table 5: Top 5 countries during various time durations based on number of publications Country Number of Publications 1977 - 2010 USA 87 China 31 Spain 18 Canada 17 United Kingdom 7 2011 - 2016 China 62 USA 48 Spain 32 Italy 21 Australia 14 2017 - 2020 China 70 USA 27 Spain 25 Italy 18 Australia 17 2021 - 2023 China 95 USA 30 United Kingdom 28 India 27 Spain 23 Thematic Analysis Thematic analysis in a bibliometric analysis technique is performed to understand the conceptual structure of the papers taken into the study. It helps identify the common research themes prevailing within a particular domain area of the study. Co-word and Co-citation analysis are some ways to perform the thematic analysis using the co-occurrences of author keywords in research studies and co-citation of research studies, respectively. A pair of research studies is treated as co-cited when at least two references are common in that pair of research studies. While the co-occurrence of keywords from authors in research studies can provide a meaningful outlook of a research theme, research studies sharing common references can also help decode a meaningful viewpoint within a research theme. In this study, the authors performed the thematic analysis by generating the thematic map from the co-occurrence of author keywords using the R-based bibliometrix tool. Since the research studies taken into this study have been divided into five phases based on their publication time, the themes that evolved during each phase have been drawn and analyzed separately. From 1977 to 1999, a major research theme focused on innovation, investment, information technology, and firm performance was drawn. From 2000 to 2010, three major research themes focused on (i) Firm Performance and Innovation, (ii) Organizational Performance and Innovation, and (iii) Dynamic Capabilities, Financial Performance, and R& D Intensity were drawn. From 2011 to 2016, five research themes were drawn, focusing on (i) Firm Performance and Innovation, (ii) Organizational Performance, Innovation, and Business value of IT, (iii) Market orientation and Innovation, (iv) Supply Chain Management, Market Orientation, Knowledge Sharing, and Diversification, and (v) Open Innovation. From 2017 to 2020, six research themes were drawn, focusing on (i) Firm Performance and social media, (ii) Firm Performance and Sustainable Development, (iii) Big Data Analytics and Firm Performance, (iv) Firm Performance and Market Orientation, (v) Firm Performance and Productivity, and (vi) Automotive Industry, Firm Performance, and Information Technology. From 2021 to 2023, two major research themes were drawn, focusing on (i) Artificial Intelligence and Firm Performance and (ii) Firm Performance and Firm Size. A comprehensive analysis of research themes within top-cited research studies that emerged during various timelines of this domain area of study has been performed in the next section, content analysis. Content Analysis 1977 – 1999 Innovation, Investment, Information Technology, and Firm Performance During 1977 – 1999, the major focus was on innovation, investment, information technology, and firm performance. Since technology was considerably a new aspect to look at and adopt for the growth of industries with the evolution of information technology during that time (Li and Richard Ye, 1999), the studies focused on understanding the relationships between IT investments and firm performance and the effects of IT investments on management objectives, business strategy, and technology policy dimensions (Weill, 1992; Zahra and Covin, 1993). Research studies also focused on understanding the impact of innovative orientation, market dynamism, and competitive intensity on the degree of customer satisfaction (Appiah-Adu and Singh, 1998), as customer satisfaction plays a crucial role in the growth of a business. While growth and profitability were the factors for which the players in the market were concerned to sustain in the industry, the studies also took into account the behavior of CEOs as to how they were able to alter the business strategies for better firm performance, as because of the intervention of technology there was a concern about an increase in the number of firms (Lefebvre, Mason and Lefebvre, 1997). In the study by, Rai et al., (1996) the authors analyzed the effect of IT on firm performance by measuring the sales, asset turnover and labour productivity. While the studies, during this time, have shown the positive as well as mediating effects of information technology on firm performance, the authors (Bartelsman, van Leeuwen and Nieuwenhuijsen, 1998; Small, 1999) also looked into the specific aspects of technological interventions such as the adoption of Advanced Manufacturing Technology (AMT) and its impact on the various aspects of firm performance. 2000-2010 Firm Performance and Innovation While the primary focus of research studies representing this theme was on innovation and how it is contributing towards the firm performance, the impact of other attributes such as entrepreneurial strategies, firm capability, internal & external capabilities, organisational culture, and internationalisation has also been taken into account. In their study, Lau & Ngo, (2004) found that HR system plays an important role in the innovativeness of the company. The authors resulted in that an HR system, focusing on reward-based work, sessions, training, and the development of team, is vital to build a great organizational culture and that will lead to build a culture of innovation in the organization. Koellinger, (2008) studied the relationship between innovation, its types, internet-based technology and their effect on firm performance. He found that all categories of innovation, encompassing both Internet-enabled and non-Internet-enabled product or process innovations, exhibit a positive relation with turnover and employment growth. Companies relying on Internet-enabled innovations are at least as prone to growth as those relying on non-Internet-enabled innovations. Although, it does not hold true in every case as research also found that innovation has not turned into a golden spoon for every industry or firm. In one such study conducted in Taiwan to assess the logistics services, the authors found that resource and innovation capability does not have positive significant effect on the performance of the firm (Yang, Marlow and Lu, 2009). Organisational Performance and Innovation While the primary focus of research studies representing this theme was on decoding organisational performance using innovation, other variables such as knowledge management, market and learning orientation, strategic flexibility were also included in these studies. In their study, Cho & Pucik, (2005) did an analysis to understand the relationship between innovativeness, quality, growth, profitability, and market value at the firm level. In an another study, (Darroch, 2005) performed a research on knowledge management which was evolving at that time and found that it can play a crucial supporting role and serve as a coordinating mechanism, thereby enhancing the transformation of resources into capabilities. The research found that these enhanced capabilities can boost the innovative potential of organizations resulting in their growth and better performance. Acknowledging the significance ascribed to information technology (IT) resources in facilitating firm innovation, the author (Benitez-Amado, Llorens-Montes and Perez-Arostegui, 2010) emphasizes that exploring the relationships between IT resources, firm innovation, and performance constitutes an important and valuable research topic. They also conducted research on the two types of IT resources i.e., technological & managerial, the culture of intrapreneurship and firm performance and found that both the types of IT resources positively influence organizational performance by enhancing the capability of culture of intrapreneurship. Dynamic Capabilities, financial performance, and R& D Intensity The focus of research studies representing this theme was on dynamic capabilities, supply chain capabilities enabled by digitalisation, ambidexterity of technology, technology sourcing, organisation learning, and financial performance of firms. In their study (Tippins and Sohi, 2003), the authors found that role of organizational learning is crucial in mediating the effects of IT competency on the performance of firm. In their research, Bhatt & Grover, (2005) resulted in identifying the importance of relationship infrastructure in facilitating the marketplace differentiation and the importance of organisational culture (dynamic capability) in enhancing the IT capabilities. The study of Lin et al., (2006), focused on technology enabled firms and their performance. In particular, their investigation focused on the primary impacts of R&D intensity, knowledge stocks, and commercialization orientation on firm performance, along with exploring the interaction effects among these variables and the findings indicate that firms within distinct technology categories should adopt varied technology commercialization strategies. The synergy between commercialization orientation and R&D intensity is evident, with a firm's commercialization orientation potentially playing a more significant role than R&D in realizing the value of technology assets. The process of commercializing a firm's technology assets, encompassing knowledge flows and knowledge stocks, is intricate, and there is no universally optimal strategy applicable to all firms. 2011-2016 Firm performance and Innovation Within this theme, the major focus of the research studies was on evaluating the effects of innovation and its various aspects on firm performance. These studies also considered the effect of other aspects such as dynamic capabilities, strategic orientations, IT competency, and marketing capabilities while examining the impact of innovation on firm performance. In their study, Mithas et al., (2012) mentioned that, in terms of IT expenditures, the findings suggest that firms should prioritize IT projects with the potential for revenue growth over those primarily focused on cost considerations. However, in an another study, Hashi & Stojčić, (2013) found that, larger firms invests more in innovation activities but also at the same time the output received by innovation might decrease by the size of the firm. The variations in the behaviour, attributes, and performance of the firms in different countries have also been observed in research studies while studying the impact of innovation on firm performance. Therefore, the research suggests that strategy adopted by firms at the time of adopting innovation should be very crucially examined. The analysis of a study (Chang, Hughes and Hotho, 2011) indicates that in a highly dynamic environment, internal organizational structures encourage the emergence of innovation ambidexterity. Furthermore, it has been observed that the connection between organizational and environmental factors and firm performance is partly mediated by a balance dimension of innovation ambidexterity. Organizational Performance, Innovation, and Business value of IT Camisón & Villar-López, (2014) analysed that the innovation practices at organization level promotes the cultivation of technological innovation capabilities. Additionally, both organizational innovation & technological capabilities, specifically for products and processes, can contribute to better performance of the organizations. McDermott & Prajogo, (2012) discussed about the ambidextrous innovation and its relationship with firm performance and discovered that both of them had a positive relationship, also specified the synergy between exploitation and exploration but they were moderated by the size of the firm. Bolívar-Ramos et al., (2012), in their analyses, found that, if top management adopt technology, it positively influences the organisational learning and technological competencies and they together promote organizational performance. However in a research, Bayo‐Moriones et al., (2013) observed that adoption of information and communication technologies (ICT) in many situations does not increase the firm performance immediately. It might take some time for resulting in the positive or negative effects of ICT implementation on organizational performance. Therefore, the management teams of the organization should have patience while implementing the ICT in their organizations. Market orientation and innovation While the major focus of the research studies representing this theme was on market orientation and innovation, several other aspects of organizational performance such as knowledge competence, sales force, technological opportunism, and market intelligence were also linked and examined. Technological opportunism has been described as the ability of firms to detect and adapt to shifts in technologies (Sarkees, 2011). The authors found that technological opportunism has a strong positive influence on vital elements of firm performance (sales of firm, profits and market-value). Similarly, e-marketing capability also has a positive influence on the performance of the firm which at the same time improves the customer satisfaction and retention (Trainor et al. , 2011). It was also found that to cultivate market orientation and market based innovations, knowledge competencies can act as a mediator (Ozkaya et al. , 2015). But the firm should understand this that, merely just by adopting doing the investments in I.T cannot help them in better performance of firm, Inspite they should also have the ability to optimise business processes (Peng et al. , 2016). On the other hand, the importance of sales force was also studied and the results indicated that impact of sales force creativity on performance is completely mediated by the implementation of innovation, and this process is further strengthened by fostering an organizational culture that encourages innovation (Wang and Miao, 2015). Supply chain management, market orientation, knowledge sharing and diversification The research studies in this theme largely focuses on the supply chain management, technology and their effect on firm performance. Attributes like building procurement, capability, electronic commerce adoption, entrepreneurial orientation have also been discussed by the different authors in their research studies. Research has described the supply side electronic integration (SEI) as the utilization of electronic methods to integrate the exchange of information and transactions with suppliers through enterprise systems and it helps in achieving two targets of customer service: minimisation of costs and increase in revenue (Xue, Ray and Sambamurthy, 2013). The findings of a study by Abebe, (2014) validate that the endorsement of e-commerce has a notable and positive impact on the average sales growth rate of SMEs. Those who endorse e-commerce technology demonstrate a significantly higher average sales growth rate compared to those who don’t adapt to the same. Despite having a general consensus that IT helps in improving the firm performance, research found that it is purely contextual and also depends on different other organizational attributes. Therefore, firms should always explore various important attributes of impacting organizational performance rather than limiting themselves only to investment in IT and hoping that it will boost their performance (Peng et al. , 2016). Open Innovation The concept of Open Innovation was introduced by Chesbrough W Henry, (2003). However, it came into practice a little later and hence it came as a theme in 2011-2016. The major focus of research studies representing this theme was on open innovation including knowledge integration capability, external collaboration, and market turbulence. Research has described the open innovation as a purposeful pursuit and integration of external inputs for new product development, that provides an alternative perspective on the innovation process (Sisodiya, Johnson and Grégoire, 2013). Authors segregated the open innovation in two dimensions: outbound i.e., internal knowledge exploitation and inbound open innovations i.e., external knowledge acquisition (Caputo et al. , 2016) and these dimensions have been helpful while making managerial decisions (Wu, Lin and Chen, 2013). The results from a study conducted by Sisodiya et al., 2013 was that the anticipated outcomes, indicating that the capacity to establish interfirm relationships in a knowledge-rich environment enhances the effectiveness of inbound open innovation for achieving superior financial performance and there is a need to distinguish various types of open innovation practices while dealing with new product development (Rubera, Chandrasekaran and Ordanini, 2016). 2017-2020 Firm Performance and social media The research studies representing this theme focused on managerial practices, organizational innovation, brand orientation, corporate entrepreneurship and social media. With the use of social media, the small and medium enterprises (SME) were able to communicate to their stakeholders and revert to competitors in a cost-effective manner. In a study conducted in UAE revealed that, social media had no impact on the performance of SMEs but it supported managers in the decision making process and other aspects (Ahmad, Abu Bakar and Ahmad, 2019). Firms have now started using social media as medium to access knowledge from outside and to analyse the same. In their study, the authors (Corral de Zubielqui, Fryges and Jones, 2019) found that social media has positive influence on attracting knowledge from the outside parties, which further impacts the innovativeness of the firm. However, these both attributes depend on the innovativeness of human resource management of an organization. Research has also found that social media influences all aspects of corporate entrepreneurship and support in better firm performance (Martín-Rojas, Garrido-Moreno and García-Morales, 2020). Firm Performance and Sustainable Development The topics researched by the research studies representing this theme were largely related to sustainable development but also included corporate social development (CSR), internationalisation, innovation, and networking. Adopting technology was not just a way for survival of businesses but also a way to include new economic activities to sustain in the market and perform better. In a study conducted by Guerrero‐Villegas et al., (2018), the authors mentioned that in a swiftly evolving environment, companies are compelled to explore novel responses to not only survive but also thrive and in their study it was revealed that CSR & innovation are a crucial mediator in the performance measurement of firms. However, Bocquet et al., (2017) focused that not just CSR activities but strategic CSR activities are crucial for the firm growth via product and process both. To maintain and grow in sustainable development in micro firms, it is crucial to maintain customer and supplier relationship with the help of innovation (Shafi, 2020). Big Data Analytics and firm performance The research studies representing this theme largely focused on big data analytics and its impact on firm performance. Maroufkhani et al., (2020) mentioned that big data analytics (BDA) is an essential component of technology and has the capability to strengthen the performance of businesses. The findings provide support for a mediation effect of BDA in the relationship between technological, organizational, and environmental contexts and SMEs performance (Maroufkhani, Wan Ismail and Ghobakhloo, 2020) and a positive impact on financials of the business (Raguseo and Vitari, 2018). To achieve this, maintaining the quality of BDA was also important. Fosso Wamba et al., (2019), in their research study, found that, to maintain the quality of BDA, quality of perceived technology, talent & information is essential, as they have a mediating effect. They also find that the alignment between quality of analytics and strategy of firm moderates the relationship between quality of big data analytics and performance of firm. Firm Performance and Market Orientation The research studies part of this theme had their focus largely on market orientation, innovation commercialisation capability, market and entrepreneurial orientation, and absorptive capacity. Kocak et al., (2017), in their study, described market orientation (MO) as a tool which helps in the reduction of tightness between exploration & exploitation of strategies by generating an opportunity for cross-fertilisation & supportive learning between strategies of innovation. The findings of their study was while responsive market orientation greatly influences incremental innovation, proactive market orientation and technology orientation support radical innovation while Lim et al., (2017) studied another aspect and results were that in the relation of market orientation and firm performance. Supply chain influence (SCI) had a moderate influence and this relationship was strong when SCI was on the higher side. Whereas innovation commercialisation capability was increased when SCI was on lower side. In a study by Migdadi et al., (2017), the study findings suggest that active participation in market orientation can result in enhanced innovation capabilities within organizations, subsequently translating into improved overall performance of firm. Firm Performance and Productivity The broad areas covered by the research studies under this theme were productivity, including innovation, customer involvement capability, organisation culture, social media and customer-centric technology. With rapid alterations in the technology and business environment, businesses need to adapt to the changes and alter their strategies, both internal and external (Anning-Dorson, 2017). Their study analysed the relationship of market demand on innovation-firm performance in service firms and found that although presence of product innovation has positive effect on the performance of firm but decreased market demand down and has a negative effect. However to bring back the positive relationship, the ability of a service firm to construct an innovative culture that support strategy management is crucial. Fu et al., (2018) discovered that innovation positively influences the productivity of labour in firms where technological innovations are on higher side than managerial innovations. Also, formal firms are less inclined towards productivity as compare to informal firms, although the aspect of innovation on productivity in formal firms has a greater impact than informal firms. Automotive Industry, Firm Performance, and Information Technology Automotive industry, IT, and Supply chain had been the major focus of research studies representing this theme. Research has defined IT as a largely accepted vital element in supply chain as to accord with the performance of independent firms & supply chain overall (Fuchs et al. , 2018). The features of IT has a significant moderation effects on the relationship of firm performance & supply chain capability (Oh, Ryu and Yang, 2019). The importance of supply chain in Indian market was explained to fulfil the customer satisfaction (Gorane and Kant, 2017). Therefore, the firms should focus on top supply chain application and not just manufacturing process. It was examined that blockchain technology can help better in enhancing the performance and other aspects of supply chain, which would ultimately increase the performance of the firm (Sheel and Nath, 2019), resulting in the positive impact of technology usage in supply chain on the firm performance. 2021-2023 Artificial Intelligence and Firm Performance The major focus of research studies representing this theme was on artificial intelligence (AI) with other elements such as IT and supply chain and blockchain technology. Research demonstrates that AI happened to be a first priority of firms as a profit of 270% was observed in the previous four years (Mikalef and Gupta, 2021) after the implementation of AI. The authors tested a model and found that with use of AI there is an increase in the creativity and performance of firms but still there are firms which are struggling with the usage of AI. To throw a more light on this Lee et al., (2022) conducted a study and found that not just AI but adequate investment in related technologies is also important to conduct research and development (R&D) within the organisation; both of them have a positive impact on the performance of the firm. Supportive the results from other research studies covering this theme, Mishra et al., (2022), in their study in U.S, finds that there is an improvement in the performance of firms with the usage of AI but it is also affecting the creation of new jobs i.e., the new job roles are reducing. Firm Performance and Firm Size Firm size, innovation, transition economies, creativity, employment growth, and manufacturing firms were the primary focus of research studies representing this theme. To understand the relationship of firm size and firm performance, Weinzimmer et al., (2023) studied it with the help of strategic aggressiveness & discovered that connection between performance of firm and strategic aggressiveness is higher in small firms as compared to that of big firms. Bringing in innovation, Mabenge et al., (2022) found that the influence of marketing innovation on the financial performance of the firm is stronger in larger firms. Research suggest that younger & large firms should use marketing innovation as a tool to increase their financial performance. On the other hand, old & small firms should be careful while attempting to use it as tool for improving their financial health. Noone et al., (2022) discussed about how decentralised culture has a positive and indirect impact on firm performance by influencing the extent of incremental product innovation, and this influence is subject to moderation by the size of the firm. It was found that superior performance effects in larger firms are attributed to their access to a network of interconnected resources, facilitating rapid diffusion of innovation even during the difficult times. Discussion Since technology was substantially a new facet to look at for advancing the progress of industries during 1977–1999, the major focus of top-cited research studies during that time was on understanding the basic consequences of adopting information technology in terms of impacting the firm performance. Therefore, the authors from these studies researched into how making a commitment to adopting information technology leads to changing business strategies, taking consideration of managers’ and stakeholders’ interests, and eventually looking into the performance implications of these IT investments. Powell and Dent-Micallef, ( 1997 ) in their study, identified that the consistent presence of standalone IT systems does not necessarily lead to sustained performance advantages for retail enterprises. Nevertheless, certain enterprises have succeeded in gaining advantages by strategically utilizing IT to leverage intangible, complementary resources. This includes fostering a flexible organizational culture, integrating strategic planning with IT initiatives, and cultivating robust relationships with suppliers. Similarly, (Bharadwaj, Bharadwaj and Konsynski, 1999 ) used Tobin’s q method to explore the relationship between investments in information technology (IT) and firm q values and found that technology plays an important role in shaping the future performance of the firm. Later, in a study by (Weill, 1992 ) the two dimensions of IT investment were studied: transactional IT investment and strategic investment in IT. The results indicated that a strong correlation exists between a substantial emphasis on transactional IT investment and robust firm performance, whereas a significant dependence on strategic IT investment seems to have a neutral effect on firm performance in the long run. The implications of technology policy were another aspect studied by (Zahra et al., 2009 ) along with business strategy and firm performance. And it was found in their study that there is notable diversity in technology policy choices among firms with distinct business strategies. Furthermore, the findings emphasize that business strategy plays a crucial role in influencing the relationship between firm performance and specific technology policies. The diversification strategies were studied by (Hill and Snell, 1988 ) and their results indicated that there is a positive correlation between innovation and higher firm profitability when compared to diversification. They find that as the investments in information technology leads to better firm performance, firms also need to strike a balance in managing the expectations of managers and stakeholders with the firms while formulating strategies. The substantial growth of these IT related investments at various levels of firm encouraged the researchers to look at the performance implications of these specific firm-level IT investments, which is quite evident from the top-cited research studies published during 2000–2010. These research studies focused on various aspects like how developing the IT capabilities and creating technology assets within the firm can lead to better firm performance, how enabling supply chain integration through technology can impact the firm performance, and how partnering with innovative ventures can add value to the partnering organization resulting in improved firm performance. (Bharadwaj, 2000 ) studied the resource-based view of the firm and argues that exceptional financial performance is intricately tied to organizational resources and capabilities. The results indicate that companies with robust IT capability consistently outperform a control sample of firms across various performance metrics related to both profit and cost. (Rai, Patnayakuni and Seth, 2006) constructed a research model to investigate the hierarchy of IT-related capabilities and their impact on firm performance. The results indicate that firms with integrated IT infrastructures have the ability to cultivate advanced capabilities in supply chain process integration. This capability enables companies to separate information flows from physical flows, collaborate effectively with their supply chain partners, and implement information-based approaches for superior demand planning, efficient staging and movement of physical products, as well as the optimization of extensive and intricate financial processes. Whereas, (Christmann, 2000 ) investigated the essential requirement of complementary assets for attaining cost advantages through the adoption of best practices. As a result, these assets play a moderating role in the connection between the adoption of best practices and the attainment of cost advantages, a pivotal factor influencing overall firm performance. There was also an impact of the internal and external networks on the performance of technological start-up companies (Lee, Lee and Pennings, 2001 ). Later, (Stuart, 2000 ) examined the relation between intercorporate technology alliances and firm performance. the findings suggest that alliances can be viewed as access relationships and argues that the advantages a focal firm derives from its strategic coalition portfolio depend on the resource profiles of its alliance partners. The findings, based on models of sales growth and innovation rates in a substantial sample of semiconductor producers, confirm that organizations with large and innovative alliance partners tend to outperform comparable firms lacking such partnerships. Consistent with the arguments related to status transfer, the results also indicate that young and small firms derive greater benefits from large and innovative strategic alliance partners than their older and larger counterparts. The top-cited research during 2011–2016 focused on understanding the implications of type of innovations such as product innovation, process innovation etc. on the different dimensions of firm performance like market, financial, and production etc. The top-cited research during this timeline also researched about how various aspects related to the working of an organization like agility and knowledge sharing etc. can contribute towards building the technology and information management capability of the organization resulting in the improved organizational performance. (Gunday et al., 2011 ) studied a theoretically grounded framework, validated through empirical testing, delineating the connections between various types of innovations and firm performance, employing an integrated innovation-performance analysis. The results highlight the favourable impact of innovations on firm performance in the manufacturing sector. (Tallon and Pinsonneault, 2011 ) studied the correlation between alignment and agility. The research establishes a positive and significant link between alignment and agility, as well as between agility and firm performance. Moreover, the study finds that the impact of alignment on performance is entirely mediated by agility. Furthermore, the study reveals that environmental volatility positively moderates the relationship between agility and firm performance, with agility having a more pronounced impact on performance in more volatile markets. (Akter et al., 2016 ) examined the capability of Big Data Analytics (BDAC) to enhance firm performance. To address this issue, the authors have proposed a model based on the Resource-Based Theory (RBT) and the entanglement view of socio-materialism. The results depict BDAC as a hierarchical model consisting of three main dimensions (management, technology, and talent capability) and 11 subdimensions (planning, investment, coordination, control, connectivity, compatibility, modularity, technology management knowledge, technical knowledge, business knowledge, and relational knowledge). The findings also emphasize the substantial moderating influence of alignment between analytics capability and business strategy on the relationship between Big Data Analytics Capability (BDAC) and firm performance (FPER). (Wang and Wang, 2012 ) studied the quantitative relationship between knowledge sharing, innovation, and performance. The findings suggest that both explicit and tacit knowledge-sharing practices play a role in fostering innovation and performance. Explicit knowledge sharing demonstrates more significant effects on the speed of innovation and financial performance, while tacit knowledge sharing has more pronounced effects on the quality of innovation and operational performance. (Mithas, Ramasubbu and Sambamurthy, 2011 ) draws on insights from the business value of IT and quality management literature to establish a link between information management capability and firm performance. The findings suggest that information management capability plays a crucial role in developing other firm capabilities related to customer, process, and performance management. Consequently, these capabilities have a positive impact on various dimensions of firm performance, including customer satisfaction, financial outcomes, human resources, and organizational effectiveness measures. Emergence of technology-based new applications like big data analytics has also caught attention of researchers during this period, which is evident from the top-cited research of 2011–2016 and 2017–2020 that draws insights from the research on how big data analytics capability of an organization can impact their performance. the dimensions studied were almost the same as in the third phase, with a little twist in them and somewhat similar findings. (Wamba et al., 2017 ) studied Big Data Analytics Capability (BDAC) grounded in the resource-based view and incorporating insights from the literature on big data analytics (BDA), information system (IS) success, and the business value of information technology (IT). The findings support the conceptualization of the hierarchical BDAC model, demonstrating both direct and indirect impacts on FPER. Moreover, the results underscore the substantial mediating role of PODC, offering valuable insights and contributing to enhanced firm performance. The study concludes by outlining practical and research implications. (Rajapathirana and Hui, 2018 ) discussed innovation, and the findings of the study suggest that the effective management of innovation capability can lead to more impactful innovation outcomes, thereby enhancing overall performance and providing managerial benefits for insurance companies and (Cai and Li, 2018 ) studied eco-innovation, the results of the study indicated that specific factors, such as technological capabilities, environmental, organizational capabilities, market-based instruments, competitive pressures, and customer green demand, contribute to the adoption of eco-innovation. The findings of (Tang et al., 2018 ) indicate that green process innovation and green product innovation significantly and positively predict firm performance when not considering managerial concern for the environment. However, once managerial concern is taken into account, it was observed that it enhances the positive effect of green process innovation on firm performance. On the other hand, green product innovation no longer explains significant unique variances in firms’ performance. (Ben Arfi, Hikkerova and Sahut, 2018 ) studied the dynamics between internal and external knowledge sharing in the context of green innovation and assesses its impact on organizational performance. The empirical findings reveal that various types of external knowledge do not yield equivalent outcomes in terms of green innovation. Additionally, the success of the innovation process is significantly influenced by the access to knowledge sources, particularly the integration of internal and external knowledge at each stage of the green innovation process. The success of green innovations reflects the organizational absorptive capacity of external knowledge and its conversion into internal skills. However, it is acknowledged that risks associated with knowledge transfer can potentially hinder the positive relationship between green innovation and firms' performance, leading to the financial failure of green innovations. During this time, environmental concerns have also emerged as the priority of researchers pursuing their research in the area of technology as an enabler to entrepreneurial performance. It resulted in research studies focusing on eco-innovation, green innovation and their implications on firm performance, which is evident from the top-cited research studies published during 2017–2020 and 2021–2023. Research evidenced the significant and positive impact of green product and process innovations on the firm performance. However, this impact is influenced by the firm’s access to internal and external knowledge sources. Top-cited research published during 2021–2023 has also focused their attention on emerging technology areas like artificial intelligence, and social media, etc. and their contribution towards the organizational performance. Research found that how an organization’s ability to quickly adapt with the technology changes of the time like building artificial intelligence capability, using social media, and innovating their business models can heavily impact their performance. During this phase, (Mikalef and Gupta, 2021 ) proposed a theoretical framework incorporating Artificial intelligence (AI) and its capability with organizational creativity and enhanced performance. The empirical results validate the proposed theoretical framework and corresponding instrument, confirming that an AI capability is associated with increased organizational creativity and enhanced performance. (Tajvidi and Karami, 2021 ) introduced a novel perspective on the impact of social media usage in Small and Medium-sized Enterprises (SMEs). The results reveal a positive and significant relationship between social media usage and firm performance. Furthermore, the findings emphasize that marketing capabilities, particularly in branding and innovation, play a positive and significant mediating role in the connection between social media usage and firm performance. (Gu, Yang and Huo, 2021 ) investigated the cultivation of supply chain (SC) resilience and its potential positive impact on firm performance and the delivery of customer value are subjects of uncertainty. The results suggest that both supplier and customer resilience can enhance SC performance, with only explorative use of IT with suppliers and customers showing significant effects. Additionally, ambidextrous use of IT on the customer side is found to be effective, and the exploitative and explorative use of IT complements each other in improving customer resilience. These findings contribute to the literature on both IT and SC resilience. (Singh et al., 2022 ) delves into the direct and indirect relationships among stakeholder pressure, green dynamic capabilities, green innovation, and the performance of small and medium-sized enterprises (SMEs) in emerging markets. The results reveal that stakeholder pressure influences green dynamic capability, which, in turn, affects green innovation and ultimately influences firm performance. Furthermore, the findings suggest that green dynamic capability mediates the influence of stakeholder pressure on green innovation, and green innovation mediates the impact of green dynamic capability on firm performance. The study's outcomes carry significant implications for both theoretical understanding and practical applications. (Clauss et al., 2021 ) focused on the organizational antecedents of business model innovations (BMIs). The results indicate a positive relationship between strategic agility and BMI, strengthened by the degree of environmental turbulence. Furthermore, while value proposition and value creation BMIs are positively related to firm performance, value capture innovation shows a negative relationship with firm performance, contrary to predictions. The findings also suggest that BMI is an important intermediary mechanism through which a firm's strategic agility contributes to superior performance. Conclusion The current study has performed performance analysis technique in bibliometric analysis to understand the publication pattern of research studies and identify the most cited authors, research studies, most impactful journals, institutions, and countries studying the role of technology as an enabler to the entrepreneurial performance. Figure 1 reflects that how authors’ inclinations towards studying the impact of technology-related interventions on the performance of entrepreneurial ventures has increased over the period of time. Tables 1 to 5 represents the various performance metrics for the research studies taken into this study and offer meaningful understanding about top cited research studies of this domain along with increasing awareness about various authors, countries, and institutions offering their meaningful contribution to this area of research inquiry. The current study also uses the co-word analysis using author keywords in bibliometric analysis to identify the emerging themes from the research studies published during different timelines, taken into this research study. Content analysis section of this research study summarizes the findings from each emerging theme during different timelines. Looking at these themes, it can inferred that while the research studies during the initial period (1977–1999) focused on basic aspects of investment in technology and how this investment is leading towards changing the business strategies to further result in impacting the firm performance, research studies during later periods focused on more mature aspects of technology interventions like technology capability, innovation capability, types of innovations, environmental aspects of innovation, application of technology into supply chain, etc. along with the specific emerging technology-based application like social media, artificial intelligence, big data analytics, blockchain etc. and their implications on various aspects of entrepreneurial performance. Firm performance and innovation, Organizational performance and innovation emerged as the central theme during 2000–2010 and 2011–2016. However, the focus of research during 2000–2010 was also on research and development intensity, firm’s ability to utilize their knowledge resources, and building an organizational culture of innovation to further impact the organizational performance. Research studies during 2011–2016 also focused on market orientation aspects of the firm, implications of technology into enabling supply chain integration, knowledge sharing, and open innovation and their relationship with the various aspects of firm performance. Research studies during 2017–2020 and 2021–2023 focused on the most recent technological interventions like emergence of social media, artificial intelligence, big data, blockchain, etc. and their impact on entrepreneurial performance. The development of AI from conceptual algorithms to tangible business solutions is noteworthy. Sectors from e-commerce to healthcare have been transformed through machine learning models, predictive analytics, and automation tools (Brynjolfsson and Mcafee, 2014 ). The transition was not solely focused on improving efficiency; rather, it was characterized by a push towards personalization and the adoption of real-time solutions. Start-ups embraced AI to optimize supply chains, elevate customer experiences, and guide strategic decision-making (Chibuike Daraojimba et al., 2023 ). They also researched about how various technological interventions are helping firms with improving their performance and sustainable development. The current study also utilizes the top-cited research studies from each theme to look at the pattern of theoretical foundations, regions studied and statistical methods used while measuring and analyzing the relationships between various aspects of technological interventions and entrepreneurial performance through empirical research. Figure 2 shows the key theories, regions studied, and methodology used in research studies linking technology and entrepreneurial performance since 1977. Most research studies have utilized the resource-based view, knowledge-based view, game theory, contingency theory, innovation-diffusion theory, and technology-organization-environment (TOE) theory as theoretical foundations to build their research frameworks and test the relationship among the constructs relevant to their studies linking technology and entrepreneurial performance. Structural equation modelling and regression analysis were commonly applied as statistical methodology in most of the research studies to analyze the collected data. While majority of the empirical research linking technology and entrepreneurial performance was performed covering different nations of Europe, a significant amount of research studies has also been performed in the national contexts of USA and China. In Europe itself, Spain was the most studied nation by the researchers and scholars in terms of performing empirical research linking technology and entrepreneurial performance. In most of the research studies, firm performance has been measured as a multi-item scale covering both financial and non-financial aspects of an entrepreneurial organization. Looking at the research combining all the timelines taken into this study, the investment in information technology and using technology-based emerging applications like social media cannot always ensure the improvement in the firm performance. It is the firm’s ability to channelize the technology-based efforts in a direction to reap the best benefits out of them. Research evidenced that while application of social media cannot guarantee and result in direct improvement in the firm performance, it can help the small and medium-sized enterprises (SMEs) leverage the social media to connect better with their stakeholders. Contribution, Limitation, and Future Scope This research study contributes to the entrepreneurship literature by exploring the different dimensions of the empirical research like common themes, constructs, and theoretical foundations linking empirical research on technology and entrepreneurial performance. This will further encourage the researchers and scholars in this field to deepen their understanding of this domain and take insights for future research studies. The novelty of this research study is in its approach to reviewing the empirical literature linking technology and entrepreneurial performance, which is a grey area for this domain of research study. Another novelty of this research study is in reviewing the literature in a systematic and phase-wise manner and offering critical insights by mapping the literature across various timelines. However, there are two intrinsic limitations to the results of this study. First, the sample under analysis comprises of research studies only in English-language and from the journals that are indexed in the Scopus database as well as having a rating in ABDC rating of journals. Further, only those research studies have been taken into the current study, that has received at least one citation, with an exemption to the recent research studies published in 2023. Subsequent research endeavors could broaden the scope of the document search to encompass journals from diverse databases and ratings, as well as books, book chapters, conference proceedings, and documents published in many languages. They can also include the research studies having no citations. Second, a wider range of previously published empirical research linking technology and entrepreneurial performance is captured by the search phrase used for database exploration. 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07:14:15","extension":"html","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":238860,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8631639/v1/16846400ce2693751dff8c6e.html"},{"id":100759173,"identity":"8203edca-4429-4df8-82f5-063de99cce64","added_by":"auto","created_at":"2026-01-21 07:13:56","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":59704,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eResearch studies published per year based on their ABDC rating (Source: Author)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8631639/v1/2303e14cda6412198d1cf88d.jpg"},{"id":100759138,"identity":"737ab3d2-b5fc-449b-b17e-84a6b2e3c19d","added_by":"auto","created_at":"2026-01-21 07:12:45","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":72785,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKey theories, regions studied, and methodology used (Source: Author)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8631639/v1/716b520ec725a460939f0760.jpg"},{"id":100760202,"identity":"804f5bd3-8097-4677-a8e0-9b75d4e67049","added_by":"auto","created_at":"2026-01-21 07:23:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1358561,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8631639/v1/82b79a72-c256-45e6-a1cf-6fb832a7792c.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eTechnology as an Enabler to Entrepreneurial Performance: Evidence from Past Literature of Quantitative Research\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eEntrepreneurs are believed to be creative, innovative, and risk-takers in their approach to driving growth for their entrepreneurial ventures (Zhao, Seibert and Lumpkin, \u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Lagu\u0026iacute;a, Moriano and Gorgievski, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Falahat, Soto-Acosta and Ramayah, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). While the last few years have witnessed rapid growth and advancements in technology, it has also put a great emphasis on entrepreneurs utilizing these technological innovations in their entrepreneurial ventures (Makridakis, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). This has resulted in an increase in studies focusing on the impact of constructs related to technology, artificial intelligence, and innovation on entrepreneurial performance (Chatterjee, Dutta Gupta and Upadhyay, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Fang et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Tran and Murphy, \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The concept of entrepreneurial performance is a widely recognized concept in the literature of entrepreneurship. Measuring entrepreneurial performance shows how effectively entrepreneurs' efforts and the ecosystem's support to entrepreneurs are getting paid off because entrepreneurship is considered to be a driver of employment generation and bringing socio-economic prosperity to economies. Entrepreneurial performance measures the performance of an entrepreneurial venture using several parameters comprising financial and non-financial characteristics (D\u0026iacute;az-Pichardo, Ju\u0026aacute;rez-Luis and S\u0026aacute;nchez-Medina, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Whereas prior research in the area of measuring entrepreneurial performance has linked it to several factors like personality traits, entrepreneurial orientation, firm strategy, networking ability, and many others (Zhao, Seibert and Lumpkin, \u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Lechner and Gudmundsson, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Karami and Tang, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Fang et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), recent literature has also shown significant interest in understanding the impact of technology adoption, innovation capability, and related variables on the performance of entrepreneurial ventures in order to understand better what drives the entrepreneurial performance. This research study attempts to synthesize the published empirical literature linking technology to entrepreneurial performance and perform a systematic review to identify common themes, constructs, theoretical foundations, and future directions for the research.\u003c/p\u003e \u003cp\u003eReviews play a crucial role in the progression of a research area through summarization of the published literature in that specified area and bringing noble insights for future research (Bland, Meurer and Maldonado, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). While earlier attempts to synthesize, summarize, and connect the research on entrepreneurial performance have explored it from the perspectives of its relationship with personality, entrepreneurial intentions, entrepreneurial learning, and human capital interventions (Zhao, Seibert and Lumpkin, \u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Tseng, \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), the authors have not come across research that has performed a systematic review for the link between technology and entrepreneurial performance using bibliometric analysis, especially in the context of researches that have utilised quantitative methods. The importance of entrepreneurial performance as a fundamental concept in the entrepreneurship literature and its association with technology encourages us to explore it from the perspective of its relationship with technology interventions (Kwun and Jeong, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Poudel, Carter and Lonial, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Using a systematic methodology, we aim to recognize the key research areas and directions of earlier quantitative research linking technology and entrepreneurial performance rather than to offer a full interpretation.\u003c/p\u003e \u003cp\u003eIn conclusion, the current study aims to summarize the diverse quantitative studies connecting technology and entrepreneurial performance. We offer insights into theoretically significant topics that have gained attention in the literature through statistical methods by concentrating solely on studies evaluating hypothesized correlations.\u003c/p\u003e"},{"header":"Research Design/Methodology/Approach","content":"\u003cp\u003eTo perform the systematic review of the empirical studies linking technology and entrepreneurial performance, we adopted the PRISMA framework (Liberati \u003cem\u003eet al.\u003c/em\u003e, 2009), which advocates the four steps: Identification, Screening, Eligibility, and Inclusion for systematically sampling the articles for review. During the first step, i.e., Identification, a comprehensive literature search was performed using the Scopus database to sample the relevant research studies linking technology and entrepreneurial performance. The search string used while searching the database was: (\u0026quot;entrepre* performance\u0026quot; OR \u0026quot;firm performance\u0026quot; OR \u0026quot;SME performance\u0026quot; OR \u0026quot;enterprise performance\u0026quot; OR \u0026quot;venture performance\u0026quot;) AND (\u0026quot;Technology\u0026quot; OR \u0026quot;Innovation\u0026quot; OR \u0026quot;AI\u0026quot; OR \u0026quot;Artificial Intelligence\u0026quot;). While the term entrepre* was used to capture all the possible variations like entrepreneur, entrepreneurial, entrepreneurship, etc., we have also used similar keywords like firm, SME, enterprise, and venture performance to capture all possible research studies relevant to entrepreneurial performance. Further, we have only used keywords like Technology, Innovation, and Artificial Intelligence to limit our focus to the broader terms used in the research in reference to technology. The search results were restricted to journal articles and the English language in order to sample only high-quality and widely applicable research studies (Miller and Serzan, 1984). The bibliometric data for these sampled research studies was exported in four phases\u003csup\u003e[1]\u003c/sup\u003e, categorized by the timelines in which research studies were published. As a result, a total list of 4631 research studies (123 up to 1999, 653 during 2000 \u0026ndash; 2010, 1070 during 2011 \u0026ndash; 2016, 1221 during 2017 \u0026ndash; 2020, and 1564 during 2021 \u0026ndash; 2023) was exported. During the screening phase, the first criterion was applied to filter out the research studies that were not published in the ABDC-rated journals because the research studies published in the ABDC-rated journals are considered to be of high impact in the field of social science and are more comprehensive than any other journal ranking list (Mura and Pahlevan Sharif, 2015). The second criterion was applied to filter out the research studies which were not primarily empirical. To apply this criterion, we checked the abstracts of these research studies to verify the occurrence of one out of seven procedural keywords (\u0026lsquo;data\u0026rsquo;, \u0026lsquo;test\u0026rsquo;, \u0026lsquo;statistical\u0026rsquo;, \u0026lsquo;empirical\u0026rsquo;, \u0026lsquo;result\u0026rsquo;, \u0026lsquo;finding\u0026rsquo;, and \u0026lsquo;evidence\u0026rsquo;) as used by (Wales, Gupta and Mousa, 2013). The third filter was applied to eliminate all those research studies that have not received any citations to date. However, an exemption was made for the research studies published in 2023 while applying this criterion, as these were the most recent studies, and the chances for them to get cited were very low. After applying all three criteria during the screening phase, we were left with a total list of 2731 research studies (70 up to 1999, 483 during 2000 \u0026ndash; 2010, 699 during 2011 \u0026ndash; 2016, 670 during 2017 \u0026ndash; 2020, and 809 during 2021 \u0026ndash; 2023).\u003c/p\u003e\n\u003cp\u003eTo further verify the eligibility of these 2731 research studies for inclusion in the list of research studies for this literature review, we went through the abstracts for all the remaining studies carefully to eliminate all those research studies that were not directly linked with the impact of technology interventions on entrepreneurial performance and empirical content having mention of statistical analysis. For example, we eliminated the studies focusing on the role of venture capitalists in high-technology firms, the role of crime in the innovation potential of firms, the relationship between HR policies and practices with firm performance, meta-analytical methodologies to review the literature on innovation and organizational performance, and likewise. We have also eliminated studies that have not utilized any statistical method to analyze the data collected, as evidenced by their abstracts. After verifying the eligibility during this phase, we were left with 1531 research studies (38 up to 1999, 304 during 2000 \u0026ndash; 2010, 383 during 2011 \u0026ndash; 2016, 345 during 2017 \u0026ndash; 2020, and 461 during 2021 \u0026ndash; 2023). These 1531 research studies were then included in this study to review them through bibliometric analysis using an R-based bibliometrix tool (Aria and Cuccurullo, 2017) and content analysis to uncover the diversity of aspects covered through the empirical studies linking technology and entrepreneurial performance and present the findings for further discussion and future agenda.\u003c/p\u003e"},{"header":"Findings from Bibliometric Analysis","content":"\u003cp\u003e\u003cstrong\u003eFindings from Bibliometric Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePerformance Analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePerformance analysis in a bibliometric analysis technique is similar to profiling participants in empirical studies, although it is conducted more rigorously by employing bibliometric metrics (Donthu \u003cem\u003eet al.\u003c/em\u003e, 2021). A performance analysis is carried out in this study to uncover the following: (1) the trends in publication, (2) the most impactful research studies, (3) the top journals, (4) authors, (5) institutions, and (6) countries that have contributed significantly to the domain of this study.\u003c/p\u003e\n\u003cp\u003eIn fundamental analysis, a total of 1531 research studies were published in 396 journals by 3507 authors emphasizing the role of technology in enabling entrepreneurial performance since 1977.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOnly 127 research studies taken in this study were authored by a single author, which reflects that most of the research in this domain has been done collaboratively. 33.9% international co-authorship represents a significant proportion of the research done through cross-country collaboration. Figure 1 represents the research studies published yearly in different ratings journals per their ABDC ratings. Most of the research studies (894 research studies) taken into this study had been published in A* and A category journals. While looking at the yearly trends reveals that technology has always been a critical aspect of determining firm performance and has also been studied well in the literature on entrepreneurship since 1977, the interest of scholars in studying the link between technology and entrepreneurial performance has grown exponentially in recent times as more than 50% of the research studies, taken into this study, are published after 2016. It shows that the growing inclination of industries towards adopting the internet and digital-driven technologies like big data, cloud computing, IoT, etc., has resulted in increasing interest by scholars and researchers worldwide in studying their impact on firm performance. Since the data in this study had been collected in a phase-wise manner based on the time duration of studies published through the Scopus database, we have analyzed the remaining performance parameters like most impactful research studies, journals, authors, institutions, and countries that had contributed significantly to the domain area of this study, in the same phase-wise manner. Tables 1 \u0026ndash; 5 show these performance metrics for this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1: Top 5 research studies during various time durations based on total citations\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResearch Study\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Citations\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTC per Year\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 519px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e1977 - 1999\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003ePowell TC, 1997, Strategic Manage J\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e1492\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e55.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eBharadwaj AS, 1999, Manage Sci\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e809\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e32.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eWeill P, 1992, Inf Syst Res\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e646\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e20.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eZahra SA, 1993, Strategic Manage J\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e527\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eHill CWL, 1988, Strategic Manage J\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e490\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e13.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 519px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e2000 - 2010\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eBharadwaj AS, 2000, MIS Quart Manage Inf Syst\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e3327\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e138.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eRai A, 2006, MIS Quart Manage Inf Syst\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e1389\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e77.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eChristmann P, 2000, Acad Manage J\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e1354\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e56.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eLee C, 2001, Strategic Manage J\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e1282\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e55.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eStuart TE, 2000, Strategic Manage J\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e1247\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e51.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 519px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e2011 - 2016\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eGunday G, 2011, Int J Prod Econ\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e896\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e68.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eTallon PP, 2011, MIS Quart Manage Inf Syst\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e773\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e59.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eAkter S, 2016, Int J Prod Econ\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e726\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e90.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eWang Z, 2012, Expert Sys Appl\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e648\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eMithas S, 2011, MIS Quart Manage Inf Syst\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e635\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e48.85\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 519px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e2017 - 2020\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eWamba SF, 2017, J Bus Res\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e1075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e153.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eRajapathirana RPJ, 2018, J Innov Knowl\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e411\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e68.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eCai W, 2018, J Clean Prod\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e355\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e59.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eTang M, 2018, Bus Strategy Environ\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e55.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eBen Arfi W, 2018, Technol Forecast Soc Change\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e277\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e46.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 519px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e2021 - 2023\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eMikalef P, 2021, Inf Manage\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e202\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e67.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eTajvidi R, 2021, Comput Hum Behav\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e46.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eGu M, 2021, Int J Prod Econ\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eSingh SK, 2022, Bus Strategy Environ\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e63.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eClauss T, 2021, IEEE Trans Eng Manage\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e39.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eLooking at these metrics, it is evident from Table 1 that a maximum of the top-cited research studies in this domain area of study had been published in Strategic Management Journal (5038 total citations) and MIS Quarterly (6124 total citations). The summarized insights from these top-cited research studies is shared in brief in discussion section. Journal of Business Research (56 publications), Technology Analysis and Strategic Management (36 publications), Journal of Cleaner Production (19 publications), and Strategic Management Journal (16 publications) are some of the leading journals contributing the maximum number of research studies (see Table 2) to this domain area of study. Looking at the top authors (see Table 3) through their h_index and the total number of citations during each phase of the study, Bharadwaj AS (4136 total citations) is the only author who received the maximum number of citations combining all phases.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u003c/strong\u003e \u003cstrong\u003eTop 5 journals during various time durations based on number of publications\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"595\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eName of the Journal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Citations\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of Publications\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 595px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e1977 - 1999\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eStrategic Management Journal\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e2976\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eJournal of Business Venturing\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e1032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eEconomics of Innovation and New Technology\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eInformation and Management\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e386\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eInformation Systems Research\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e1087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 595px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e2000 - 2010\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eStrategic Management Journal\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e6424\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eJournal of Management Information Systems\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e2875\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eResearch Policy\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e2272\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eInformation and Management\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e776\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eInternational Journal of Technology Management\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e271\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 595px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e2011 - 2016\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eJournal of Business Research\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e2841\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eIndustrial Management and Data Systems\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e692\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eManagement Decision\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e681\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eTechnology Analysis and Strategic Management\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e331\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eJournal of Product Innovation Management\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e755\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 595px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e2017 - 2020\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eJournal of Business Research\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e2374\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eTechnology Analysis and Strategic Management\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e360\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eJournal of Cleaner Production\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e1550\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eTechnological Forecasting and Social Change\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eInternational Journal of Production Economics\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e634\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 595px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e2021 - 2023\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eJournal of Business Research\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e381\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eIEEE Transactions on Engineering Management\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e383\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eTechnology Analysis and Strategic Management\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eBusiness Strategy and the Environment\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e382\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cem\u003eJournal of Cleaner Production\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e231\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3:\u003c/strong\u003e \u003cstrong\u003eTop 5 authors during various time durations based on their h_index and Total Citation\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eName of the Author\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eh_index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eName of the Author\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 152px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Citation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 539px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e1977 - 1999\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eCovin JG\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eDent-Micallef A\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 152px;\"\u003e\n \u003cp\u003e1492\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eZahra SA\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003ePowell TC\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 152px;\"\u003e\n \u003cp\u003e1492\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eAlpar P\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eZahra SA\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 152px;\"\u003e\n \u003cp\u003e813\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eAppiah-Adu K\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eBharadwaj AS\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 152px;\"\u003e\n \u003cp\u003e809\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eBartelsman E\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eBharadwaj SG\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 152px;\"\u003e\n \u003cp\u003e809\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 539px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e2000 - 2010\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eByrd TA\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eBharadwaj AS\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 152px;\"\u003e\n \u003cp\u003e3327\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eKraemer KL\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eZhu K\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 152px;\"\u003e\n \u003cp\u003e2125\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eTsai K-H\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eKraemer KL\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 152px;\"\u003e\n \u003cp\u003e1749\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eZhu K\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eRai A\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 152px;\"\u003e\n \u003cp\u003e1523\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eCavusgil ST\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003ePatnayakuni R\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 152px;\"\u003e\n \u003cp\u003e1389\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 539px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e2011 - 2016\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eSambamurthy V\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eSambamurthy V\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 152px;\"\u003e\n \u003cp\u003e1297\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eLee J-N\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eMithas S\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 152px;\"\u003e\n \u003cp\u003e1258\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eMithas S\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eAlpkan L\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 152px;\"\u003e\n \u003cp\u003e896\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eCalantone RJ\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eGunday G\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 152px;\"\u003e\n \u003cp\u003e896\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eCucculelli M\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eKilic K\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 152px;\"\u003e\n \u003cp\u003e896\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 539px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e2017 - 2020\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eAnning-Dorson T\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eAkter S\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 152px;\"\u003e\n \u003cp\u003e1238\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eBao Y\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eChilde SJ\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 152px;\"\u003e\n \u003cp\u003e1075\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eWang Y\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eDubey R\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 152px;\"\u003e\n \u003cp\u003e1075\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eAkter S\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eGunasekaran A\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 152px;\"\u003e\n \u003cp\u003e1075\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eFosso Wamba S\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eRen SJ-F\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 152px;\"\u003e\n \u003cp\u003e1075\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 539px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e2021 - 2023\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eChatterjee S\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eMikalef P\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 152px;\"\u003e\n \u003cp\u003e203\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eChaudhuri R\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eGupta M\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 152px;\"\u003e\n \u003cp\u003e202\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eChen Y\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eChen Y\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 152px;\"\u003e\n \u003cp\u003e180\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eKumar S\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eDel Giudice M\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 152px;\"\u003e\n \u003cp\u003e173\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eWei Z\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cem\u003eSingh SK\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 152px;\"\u003e\n \u003cp\u003e173\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe authors affiliated with Michigan State University, USA (25 publications) have contributed the maximum number of research studies (see Table 4) to the domain area of this study. In terms of countries (see Table 5), the authors from the USA (192 publications), China (310 publications), Spain (98 publications), the United Kingdom (35 publications), and Australia (31 publications) have contributed to the maximum number of research studies, the contribution of Indian authors (27 publications during 2021 \u0026ndash; 2023) to the domain area of this study has also started increasing in recent times.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4:\u003c/strong\u003e \u003cstrong\u003eTop 5 institutions during various time durations based on number of publications\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"510\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eName of the Institution\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of Publications\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 510px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e1977 - 1999\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cem\u003eAuburn University\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cem\u003eBen-Gurion University of The Negev\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cem\u003eHebrew University of Jerusalem\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cem\u003eSTT. Univ. of New York at Buffalo\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cem\u003eSeattle\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 510px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e2000 - 2010\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cem\u003eMichigan State University\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cem\u003eNational Cheng Kung University\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cem\u003eNational Chung Cheng University\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cem\u003eUniversity of California\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cem\u003eUniversity of Tehran\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 510px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e2011 - 2016\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cem\u003eMichigan State University\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cem\u003eNational Taiwan University\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cem\u003eGriffith University\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cem\u003eLappeenranta University of Technology\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cem\u003eNational Chengchi University\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 510px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e2017 - 2020\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cem\u003eUniversity of Ghana Business School\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cem\u003eUniversity of Science and Technology of China\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cem\u003eUniversity of Murcia\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cem\u003eHuazhong University of Science and Technology\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cem\u003eNorthwestern Polytechnical University\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 510px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e2021 - 2023\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cem\u003eJiangsu University\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cem\u003eCentral South University\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cem\u003eSichuan Agricultural University\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cem\u003eUral Federal University\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cem\u003eXi\u0026apos;an Jiaotong University\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5:\u003c/strong\u003e \u003cstrong\u003eTop 5 countries during various time durations based on number of publications\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCountry\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 176px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of Publications\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 302px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e1977 - 2010\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cem\u003eUSA\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 176px;\"\u003e\n \u003cp\u003e87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cem\u003eChina\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 176px;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cem\u003eSpain\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 176px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cem\u003eCanada\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 176px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cem\u003eUnited Kingdom\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 176px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 302px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e2011 - 2016\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cem\u003eChina\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 176px;\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cem\u003eUSA\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 176px;\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cem\u003eSpain\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 176px;\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cem\u003eItaly\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 176px;\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cem\u003eAustralia\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 176px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 302px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e2017 - 2020\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cem\u003eChina\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 176px;\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cem\u003eUSA\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 176px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cem\u003eSpain\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 176px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cem\u003eItaly\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 176px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cem\u003eAustralia\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 176px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 302px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e2021 - 2023\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cem\u003eChina\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 176px;\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cem\u003eUSA\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 176px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cem\u003eUnited Kingdom\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 176px;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cem\u003eIndia\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 176px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cem\u003eSpain\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 176px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cdiv id=\"ftn1\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eThematic Analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThematic analysis in a bibliometric analysis technique is performed to understand the conceptual structure of the papers taken into the study. It helps identify the common research themes prevailing within a particular domain area of the study. Co-word and Co-citation analysis are some ways to perform the thematic analysis using the co-occurrences of author keywords in research studies and co-citation of research studies, respectively. A pair of research studies is treated as co-cited when at least two references are common in that pair of research studies. While the co-occurrence of keywords from authors in research studies can provide a meaningful outlook of a research theme, research studies sharing common references can also help decode a meaningful viewpoint within a research theme.\u003c/p\u003e\n \u003cp\u003eIn this study, the authors performed the thematic analysis by generating the thematic map from the co-occurrence of author keywords using the R-based bibliometrix tool. Since the research studies taken into this study have been divided into five phases based on their publication time, the themes that evolved during each phase have been drawn and analyzed separately.\u003c/p\u003e\n \u003cp\u003eFrom 1977 to 1999, a major research theme focused on innovation, investment, information technology, and firm performance was drawn. From 2000 to 2010, three major research themes focused on (i) Firm Performance and Innovation, (ii) Organizational Performance and Innovation, and (iii) Dynamic Capabilities, Financial Performance, and R\u0026amp; D Intensity were drawn. From 2011 to 2016, five research themes were drawn, focusing on (i) Firm Performance and Innovation, (ii) Organizational Performance, Innovation, and Business value of IT, (iii) Market orientation and Innovation, (iv) Supply Chain Management, Market Orientation, Knowledge Sharing, and Diversification, and (v) Open Innovation. From 2017 to 2020, six research themes were drawn, focusing on (i) Firm Performance and social media, (ii) Firm Performance and Sustainable Development, (iii) Big Data Analytics and Firm Performance, (iv) Firm Performance and Market Orientation, (v) Firm Performance and Productivity, and (vi) Automotive Industry, Firm Performance, and Information Technology. From 2021 to 2023, two major research themes were drawn, focusing on (i) Artificial Intelligence and Firm Performance and (ii) Firm Performance and Firm Size. A comprehensive analysis of research themes within top-cited research studies that emerged during various timelines of this domain area of study has been performed in the next section, content analysis.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eContent Analysis\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e1977 \u0026ndash; 1999\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eInnovation, Investment, Information Technology, and Firm Performance\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eDuring 1977 \u0026ndash; 1999, the major focus was on innovation, investment, information technology, and firm performance. Since technology was considerably a new aspect to look at and adopt for the growth of industries with the evolution of information technology during that time (Li and Richard Ye, 1999), the studies focused on understanding the relationships between IT investments and firm performance and the effects of IT investments on management objectives, business strategy, and technology policy dimensions (Weill, 1992; Zahra and Covin, 1993). Research studies also focused on understanding the impact of innovative orientation, market dynamism, and competitive intensity on the degree of customer satisfaction (Appiah-Adu and Singh, 1998), as customer satisfaction plays a crucial role in the growth of a business. While growth and profitability were the factors for which the players in the market were concerned to sustain in the industry, the studies also took into account the behavior of CEOs as to how they were able to alter the business strategies for better firm performance, as because of the intervention of technology there was a concern about an increase in the number of firms (Lefebvre, Mason and Lefebvre, 1997). \u0026nbsp;In the study by, Rai et al., (1996) the authors analyzed the effect of IT on firm performance by measuring the sales, asset turnover and labour productivity. While the studies, during this time, have shown the positive as well as mediating effects of information technology on firm performance, the authors (Bartelsman, van Leeuwen and Nieuwenhuijsen, 1998; Small, 1999) also looked into the specific aspects of technological interventions such as the adoption of Advanced Manufacturing Technology (AMT) and its impact on the various aspects of firm performance.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e2000-2010\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eFirm Performance and Innovation\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eWhile the primary focus of research studies representing this theme was on innovation and how it is contributing towards the firm performance, the impact of other attributes such as entrepreneurial strategies, firm capability, internal \u0026amp; external capabilities, organisational culture, and internationalisation has also been taken into account. In their study, Lau \u0026amp; Ngo, (2004) found that HR system plays an important role in the innovativeness of the company. The authors resulted in that an HR system, focusing on reward-based work, sessions, training, and the development of team, is vital to build a great organizational culture and that will lead to build a culture of innovation in the organization. Koellinger, (2008) studied the relationship between innovation, its types, internet-based technology and their effect on firm performance. He found that all categories of innovation, encompassing both Internet-enabled and non-Internet-enabled product or process innovations, exhibit a positive relation with turnover and employment growth. Companies relying on Internet-enabled innovations are at least as prone to growth as those relying on non-Internet-enabled innovations. Although, it does not hold true in every case as research also found that innovation has not turned into a golden spoon for every industry or firm. In one such study conducted in Taiwan to assess the logistics services, the authors found that resource and innovation capability does not have positive significant effect on the performance of the firm (Yang, Marlow and Lu, 2009).\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eOrganisational Performance and Innovation\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eWhile the primary focus of research studies representing this theme was on decoding organisational performance using innovation, other variables such as knowledge management, market and learning orientation, strategic flexibility were also included in these studies. In their study, Cho \u0026amp; Pucik, (2005) did an analysis to understand the relationship between innovativeness, quality, growth, profitability, and market value at the firm level. In an another study, (Darroch, 2005) performed a research on knowledge management which was evolving at that time and found that it can play a crucial supporting role and serve as a coordinating mechanism, thereby enhancing the transformation of resources into capabilities. The research found that these enhanced capabilities can boost the innovative potential of organizations resulting in their growth and better performance. \u0026nbsp;Acknowledging the significance ascribed to information technology (IT) resources in facilitating firm innovation, the author (Benitez-Amado, Llorens-Montes and Perez-Arostegui, 2010) emphasizes that exploring the relationships between IT resources, firm innovation, and performance constitutes an important and valuable research topic. They also conducted research on the two types of IT resources i.e., technological \u0026amp; managerial, the culture of intrapreneurship and firm performance and found that both the types of IT resources positively influence organizational performance by enhancing the capability of culture of intrapreneurship.\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eDynamic Capabilities, financial performance, and R\u0026amp; D Intensity\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eThe focus of research studies representing this theme was on dynamic capabilities, supply chain capabilities enabled by digitalisation, ambidexterity of technology, technology sourcing, organisation learning, and financial performance of firms. In their study (Tippins and Sohi, 2003), the authors found that role of organizational learning is crucial in mediating the effects of IT competency on the performance of firm. In their research, Bhatt \u0026amp; Grover, (2005) resulted in identifying the importance of relationship infrastructure in facilitating the marketplace differentiation and the importance of organisational culture (dynamic capability) in enhancing the IT capabilities. The study of Lin et al., (2006), focused on technology enabled firms and their performance. In particular, their investigation focused on the primary impacts of R\u0026amp;D intensity, knowledge stocks, and commercialization orientation on firm performance, along with exploring the interaction effects among these variables and the findings indicate that firms within distinct technology categories should adopt varied technology commercialization strategies. The synergy between commercialization orientation and R\u0026amp;D intensity is evident, with a firm\u0026apos;s commercialization orientation potentially playing a more significant role than R\u0026amp;D in realizing the value of technology assets. The process of commercializing a firm\u0026apos;s technology assets, encompassing knowledge flows and knowledge stocks, is intricate, and there is no universally optimal strategy applicable to all firms.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e2011-2016\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eFirm performance and Innovation\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eWithin this theme, the major focus of the research studies was on evaluating the effects of innovation and its various aspects on firm performance. These studies also considered the effect of other aspects such as dynamic capabilities, strategic orientations, IT competency, and marketing capabilities while examining the impact of innovation on firm performance. In their study, Mithas et al., (2012) mentioned that, in terms of IT expenditures, the findings suggest that firms should prioritize IT projects with the potential for revenue growth over those primarily focused on cost considerations. However, in an another study, Hashi \u0026amp; Stojčić, (2013) found that, larger firms invests more in innovation activities but also at the same time the output received by innovation might decrease by the size of the firm. The variations in the behaviour, attributes, and performance of the firms in different countries have also been observed in research studies while studying the impact of innovation on firm performance. Therefore, the research suggests that strategy adopted by firms at the time of adopting innovation should be very crucially examined. The analysis of a study (Chang, Hughes and Hotho, 2011) indicates that in a highly dynamic environment, internal organizational structures encourage the emergence of innovation ambidexterity. Furthermore, it has been observed that the connection between organizational and environmental factors and firm performance is partly mediated by a balance dimension of innovation ambidexterity.\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eOrganizational Performance, Innovation, and Business value of IT\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eCamis\u0026oacute;n \u0026amp; Villar-L\u0026oacute;pez, (2014) analysed that the innovation practices at organization level promotes the cultivation of technological innovation capabilities. Additionally, both organizational innovation \u0026amp; technological capabilities, specifically for products and processes, can contribute to better performance of the organizations. McDermott \u0026amp; Prajogo, (2012) discussed about the ambidextrous innovation and its relationship with firm performance and discovered that both of them had a positive relationship, also specified the synergy between exploitation and exploration but they were moderated by the size of the firm. Bol\u0026iacute;var-Ramos et al., (2012), in their analyses, found that, if top management adopt technology, it positively influences the organisational learning and technological competencies and they together promote organizational performance. However in a research, Bayo‐Moriones et al., (2013) observed that adoption of information and communication technologies (ICT) in many situations does not increase the firm performance immediately. It might take some time for resulting in the positive or negative effects of ICT implementation on organizational performance. Therefore, the management teams of the organization should have patience while implementing the ICT in their organizations.\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eMarket orientation and innovation\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eWhile the major focus of the research studies representing this theme was on market orientation and innovation, several other aspects of organizational performance such as knowledge competence, sales force, technological opportunism, and market intelligence were also linked and examined. Technological opportunism has been described as the ability of firms to detect and adapt to shifts in technologies (Sarkees, 2011). The authors found that technological opportunism has a strong positive influence on vital elements of firm performance (sales of firm, profits and market-value). Similarly, e-marketing capability also has a positive influence on the performance of the firm which at the same time improves the customer satisfaction and retention (Trainor \u003cem\u003eet al.\u003c/em\u003e, 2011). It was also found that to cultivate market orientation and market based innovations, knowledge competencies can act as a mediator (Ozkaya \u003cem\u003eet al.\u003c/em\u003e, 2015). But the firm should understand this that, merely just by adopting doing the investments in I.T cannot help them in better performance of firm, Inspite they should also have the ability to optimise business processes (Peng \u003cem\u003eet al.\u003c/em\u003e, 2016). On the other hand, the importance of sales force was also studied and the results indicated that impact of sales force creativity on performance is completely mediated by the implementation of innovation, and this process is further strengthened by fostering an organizational culture that encourages innovation (Wang and Miao, 2015).\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eSupply chain management, market orientation, knowledge sharing and diversification\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eThe research studies in this theme largely focuses on the supply chain management, technology and their effect on firm performance. Attributes like building procurement, capability, electronic commerce adoption, entrepreneurial orientation have also been discussed by the different authors in their research studies. Research has described the supply side electronic integration (SEI) as the utilization of electronic methods to integrate the exchange of information and transactions with suppliers through enterprise systems and it helps in achieving two targets of customer service: minimisation of costs and increase in revenue (Xue, Ray and Sambamurthy, 2013). The findings of a study by Abebe, (2014) validate that the endorsement of e-commerce has a notable and positive impact on the average sales growth rate of SMEs. Those who endorse e-commerce technology demonstrate a significantly higher average sales growth rate compared to those who don\u0026rsquo;t adapt to the same. Despite having a general consensus that IT helps in improving the firm performance, research found that it is purely contextual and also depends on different other organizational attributes. Therefore, firms should always explore various important attributes of impacting organizational performance rather than limiting themselves only to investment in IT and hoping that it will boost their performance (Peng \u003cem\u003eet al.\u003c/em\u003e, 2016).\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eOpen Innovation\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eThe concept of Open Innovation was introduced by Chesbrough W Henry, (2003). However, it came into practice a little later and hence it came as a theme in 2011-2016. The major focus of research studies representing this theme was on open innovation including knowledge integration capability, external collaboration, and market turbulence. Research has described the open innovation as a purposeful pursuit and integration of external inputs for new product development, that provides an alternative perspective on the innovation process (Sisodiya, Johnson and Gr\u0026eacute;goire, 2013). Authors segregated the open innovation in two dimensions: outbound i.e., internal knowledge exploitation and inbound open innovations i.e., external knowledge acquisition (Caputo \u003cem\u003eet al.\u003c/em\u003e, 2016) and these dimensions have been helpful while making managerial decisions (Wu, Lin and Chen, 2013). The results from a study conducted by Sisodiya et al., 2013 was that the anticipated outcomes, indicating that the capacity to establish interfirm relationships in a knowledge-rich environment enhances the effectiveness of inbound open innovation for achieving superior financial performance and there is a need to distinguish various types of open innovation practices while dealing with new product development (Rubera, Chandrasekaran and Ordanini, 2016).\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e2017-2020\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eFirm Performance and social media\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eThe research studies representing this theme focused on managerial practices, organizational innovation, brand orientation, corporate entrepreneurship and social media. With the use of social media, the small and medium enterprises (SME) were able to communicate to their stakeholders and revert to competitors in a cost-effective manner. In a study conducted in UAE revealed that, social media had no impact on the performance of SMEs but it supported managers in the decision making process and other aspects (Ahmad, Abu Bakar and Ahmad, 2019). Firms have now started using social media as medium to access knowledge from outside and to analyse the same. In their study, the authors (Corral de Zubielqui, Fryges and Jones, 2019) found that social media has positive influence on attracting knowledge from the outside parties, which further impacts the innovativeness of the firm. However, these both attributes depend on the innovativeness of human resource management of an organization. Research has also found that social media influences all aspects of corporate entrepreneurship and support in better firm performance (Mart\u0026iacute;n-Rojas, Garrido-Moreno and Garc\u0026iacute;a-Morales, 2020).\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eFirm Performance and Sustainable Development\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eThe topics researched by the research studies representing this theme were largely related to sustainable development but also included corporate social development (CSR), internationalisation, innovation, and networking. Adopting technology was not just a way for survival of businesses but also a way to include new economic activities to sustain in the market and perform better. In a study conducted by Guerrero‐Villegas et al., (2018), the authors mentioned that in a swiftly evolving environment, companies are compelled to explore novel responses to not only survive but also thrive and in their study it was revealed that CSR \u0026amp; innovation are a crucial mediator in the performance measurement of firms. However, Bocquet et al., (2017) focused that not just CSR activities but strategic CSR activities are crucial for the firm growth via product and process both. To maintain and grow in sustainable development in micro firms, it is crucial to maintain customer and supplier relationship with the help of innovation (Shafi, 2020).\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eBig Data Analytics and firm performance\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eThe research studies representing this theme largely focused on big data analytics and its impact on firm performance. Maroufkhani et al., (2020) mentioned that big data analytics (BDA) is an essential component of technology and has the capability to strengthen the performance of businesses. The findings provide support for a mediation effect of BDA in the relationship between technological, organizational, and environmental contexts and SMEs performance (Maroufkhani, Wan Ismail and Ghobakhloo, 2020) and a positive impact on financials of the business (Raguseo and Vitari, 2018). To achieve this, maintaining the quality of BDA was also important. Fosso Wamba et al., (2019), in their research study, found that, to maintain the quality of BDA, quality of perceived technology, talent \u0026amp; information is essential, as they have a mediating effect. They also find that the alignment between quality of analytics and strategy of firm moderates the relationship between quality of big data analytics and performance of firm.\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eFirm Performance and Market Orientation\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eThe research studies part of this theme had their focus largely on market orientation, innovation commercialisation capability, market and entrepreneurial orientation, and absorptive capacity. Kocak et al., (2017), in their study, described market orientation (MO) as a tool which helps in the reduction of tightness between exploration \u0026amp; exploitation of strategies by generating an opportunity for cross-fertilisation \u0026amp; supportive learning between strategies of innovation. The findings of their study was while responsive market orientation greatly influences incremental innovation, proactive market orientation and technology orientation support radical innovation while Lim et al., (2017) studied another aspect and results were that in the relation of market orientation and firm performance. Supply chain influence (SCI) had a moderate influence and this relationship was strong when SCI was on the higher side. Whereas innovation commercialisation capability was increased when SCI was on lower side. In a study by Migdadi et al., (2017), the study findings suggest that active participation in market orientation can result in enhanced innovation capabilities within organizations, subsequently translating into improved overall performance of firm.\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eFirm Performance and Productivity\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eThe broad areas covered by the research studies under this theme were productivity, including innovation, customer involvement capability, organisation culture, social media and customer-centric technology. With rapid alterations in the technology and business environment, businesses need to adapt to the changes and alter their strategies, both internal and external (Anning-Dorson, 2017). Their study analysed the relationship of market demand on innovation-firm performance in service firms and found that although presence of product innovation has positive effect on the performance of firm but decreased market demand down and has a negative effect. However to bring back the positive relationship, the ability of a service firm to construct an innovative culture that support strategy management is crucial. Fu et al., (2018) discovered that innovation positively influences the productivity of labour in firms where technological innovations are on higher side than managerial innovations. Also, formal firms are less inclined towards productivity as compare to informal firms, although the aspect of innovation on productivity in formal firms has a greater impact than informal firms.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eAutomotive Industry, Firm Performance, and Information Technology\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eAutomotive industry, IT, and Supply chain had been the major focus of research studies representing this theme. Research has defined IT as a largely accepted vital element in supply chain as to accord with the performance of independent firms \u0026amp; supply chain overall (Fuchs \u003cem\u003eet al.\u003c/em\u003e, 2018). The features of IT has a significant moderation effects on the relationship of firm performance \u0026amp; supply chain capability (Oh, Ryu and Yang, 2019). The importance of supply chain in Indian market was explained to fulfil the customer satisfaction (Gorane and Kant, 2017). Therefore, the firms should focus on top supply chain application and not just manufacturing process. It was examined that blockchain technology can help better in enhancing the performance and other aspects of supply chain, which would ultimately increase the performance of the firm (Sheel and Nath, 2019), resulting in the positive impact of technology usage in supply chain on the firm performance.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e2021-2023\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eArtificial Intelligence and Firm Performance\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eThe major focus of research studies representing this theme was on artificial intelligence (AI) with other elements such as IT and supply chain and blockchain technology. Research demonstrates that AI happened to be a first priority of firms as a profit of 270% was observed in the previous four years (Mikalef and Gupta, 2021) after the implementation of AI. The authors tested a model and found that with use of AI there is an increase in the creativity and performance of firms but still there are firms which are struggling with the usage of AI. To throw a more light on this Lee et al., (2022) conducted a study and found that not just AI but adequate investment in related technologies is also important to conduct research and development (R\u0026amp;D) within the organisation; both of them have a positive impact on the performance of the firm. Supportive the results from other research studies covering this theme, Mishra et al., (2022), in their study in U.S, finds that there is an improvement in the performance of firms with the usage of AI but it is also affecting the creation of new jobs i.e., the new job roles are reducing.\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eFirm Performance and Firm Size\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eFirm size, innovation, transition economies, creativity, employment growth, and manufacturing firms were the primary focus of research studies representing this theme. To understand the relationship of firm size and firm performance, Weinzimmer et al., (2023) studied it with the help of strategic aggressiveness \u0026amp; discovered that connection between performance of firm and strategic aggressiveness is higher in small firms as compared to that of big firms. Bringing in innovation, Mabenge et al., (2022) found that the influence of marketing innovation on the financial performance of the firm is stronger in larger firms. Research suggest that younger \u0026amp; large firms should use marketing innovation as a tool to increase their financial performance. On the other hand, old \u0026amp; small firms should be careful while attempting to use it as tool for improving their financial health. Noone et al., (2022) discussed about how decentralised culture has a positive and indirect impact on firm performance by influencing the extent of incremental product innovation, and this influence is subject to moderation by the size of the firm. It was found that superior performance effects in larger firms are attributed to their access to a network of interconnected resources, facilitating rapid diffusion of innovation even during the difficult times.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eSince technology was substantially a new facet to look at for advancing the progress of industries during 1977\u0026ndash;1999, the major focus of top-cited research studies during that time was on understanding the basic consequences of adopting information technology in terms of impacting the firm performance. Therefore, the authors from these studies researched into how making a commitment to adopting information technology leads to changing business strategies, taking consideration of managers\u0026rsquo; and stakeholders\u0026rsquo; interests, and eventually looking into the performance implications of these IT investments. Powell and Dent-Micallef, (\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e1997\u003c/span\u003e) in their study, identified that the consistent presence of standalone IT systems does not necessarily lead to sustained performance advantages for retail enterprises. Nevertheless, certain enterprises have succeeded in gaining advantages by strategically utilizing IT to leverage intangible, complementary resources. This includes fostering a flexible organizational culture, integrating strategic planning with IT initiatives, and cultivating robust relationships with suppliers. Similarly, (Bharadwaj, Bharadwaj and Konsynski, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) used Tobin\u0026rsquo;s q method to explore the relationship between investments in information technology (IT) and firm q values and found that technology plays an important role in shaping the future performance of the firm. Later, in a study by (Weill, \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e1992\u003c/span\u003e) the two dimensions of IT investment were studied: transactional IT investment and strategic investment in IT. The results indicated that a strong correlation exists between a substantial emphasis on transactional IT investment and robust firm performance, whereas a significant dependence on strategic IT investment seems to have a neutral effect on firm performance in the long run. The implications of technology policy were another aspect studied by (Zahra et al., \u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) along with business strategy and firm performance. And it was found in their study that there is notable diversity in technology policy choices among firms with distinct business strategies. Furthermore, the findings emphasize that business strategy plays a crucial role in influencing the relationship between firm performance and specific technology policies. The diversification strategies were studied by (Hill and Snell, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e1988\u003c/span\u003e) and their results indicated that there is a positive correlation between innovation and higher firm profitability when compared to diversification. They find that as the investments in information technology leads to better firm performance, firms also need to strike a balance in managing the expectations of managers and stakeholders with the firms while formulating strategies.\u003c/p\u003e \u003cp\u003eThe substantial growth of these IT related investments at various levels of firm encouraged the researchers to look at the performance implications of these specific firm-level IT investments, which is quite evident from the top-cited research studies published during 2000\u0026ndash;2010. These research studies focused on various aspects like how developing the IT capabilities and creating technology assets within the firm can lead to better firm performance, how enabling supply chain integration through technology can impact the firm performance, and how partnering with innovative ventures can add value to the partnering organization resulting in improved firm performance. (Bharadwaj, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) studied the resource-based view of the firm and argues that exceptional financial performance is intricately tied to organizational resources and capabilities. The results indicate that companies with robust IT capability consistently outperform a control sample of firms across various performance metrics related to both profit and cost. (Rai, Patnayakuni and Seth, 2006) constructed a research model to investigate the hierarchy of IT-related capabilities and their impact on firm performance. The results indicate that firms with integrated IT infrastructures have the ability to cultivate advanced capabilities in supply chain process integration. This capability enables companies to separate information flows from physical flows, collaborate effectively with their supply chain partners, and implement information-based approaches for superior demand planning, efficient staging and movement of physical products, as well as the optimization of extensive and intricate financial processes. Whereas, (Christmann, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) investigated the essential requirement of complementary assets for attaining cost advantages through the adoption of best practices. As a result, these assets play a moderating role in the connection between the adoption of best practices and the attainment of cost advantages, a pivotal factor influencing overall firm performance. There was also an impact of the internal and external networks on the performance of technological start-up companies (Lee, Lee and Pennings, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Later, (Stuart, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) examined the relation between intercorporate technology alliances and firm performance. the findings suggest that alliances can be viewed as access relationships and argues that the advantages a focal firm derives from its strategic coalition portfolio depend on the resource profiles of its alliance partners. The findings, based on models of sales growth and innovation rates in a substantial sample of semiconductor producers, confirm that organizations with large and innovative alliance partners tend to outperform comparable firms lacking such partnerships. Consistent with the arguments related to status transfer, the results also indicate that young and small firms derive greater benefits from large and innovative strategic alliance partners than their older and larger counterparts.\u003c/p\u003e \u003cp\u003eThe top-cited research during 2011\u0026ndash;2016 focused on understanding the implications of type of innovations such as product innovation, process innovation etc. on the different dimensions of firm performance like market, financial, and production etc. The top-cited research during this timeline also researched about how various aspects related to the working of an organization like agility and knowledge sharing etc. can contribute towards building the technology and information management capability of the organization resulting in the improved organizational performance. (Gunday et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) studied a theoretically grounded framework, validated through empirical testing, delineating the connections between various types of innovations and firm performance, employing an integrated innovation-performance analysis. The results highlight the favourable impact of innovations on firm performance in the manufacturing sector. (Tallon and Pinsonneault, \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) studied the correlation between alignment and agility. The research establishes a positive and significant link between alignment and agility, as well as between agility and firm performance. Moreover, the study finds that the impact of alignment on performance is entirely mediated by agility. Furthermore, the study reveals that environmental volatility positively moderates the relationship between agility and firm performance, with agility having a more pronounced impact on performance in more volatile markets. (Akter et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) examined the capability of Big Data Analytics (BDAC) to enhance firm performance. To address this issue, the authors have proposed a model based on the Resource-Based Theory (RBT) and the entanglement view of socio-materialism. The results depict BDAC as a hierarchical model consisting of three main dimensions (management, technology, and talent capability) and 11 subdimensions (planning, investment, coordination, control, connectivity, compatibility, modularity, technology management knowledge, technical knowledge, business knowledge, and relational knowledge). The findings also emphasize the substantial moderating influence of alignment between analytics capability and business strategy on the relationship between Big Data Analytics Capability (BDAC) and firm performance (FPER). (Wang and Wang, \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) studied the quantitative relationship between knowledge sharing, innovation, and performance. The findings suggest that both explicit and tacit knowledge-sharing practices play a role in fostering innovation and performance. Explicit knowledge sharing demonstrates more significant effects on the speed of innovation and financial performance, while tacit knowledge sharing has more pronounced effects on the quality of innovation and operational performance. (Mithas, Ramasubbu and Sambamurthy, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) draws on insights from the business value of IT and quality management literature to establish a link between information management capability and firm performance. The findings suggest that information management capability plays a crucial role in developing other firm capabilities related to customer, process, and performance management. Consequently, these capabilities have a positive impact on various dimensions of firm performance, including customer satisfaction, financial outcomes, human resources, and organizational effectiveness measures.\u003c/p\u003e \u003cp\u003eEmergence of technology-based new applications like big data analytics has also caught attention of researchers during this period, which is evident from the top-cited research of 2011\u0026ndash;2016 and 2017\u0026ndash;2020 that draws insights from the research on how big data analytics capability of an organization can impact their performance. the dimensions studied were almost the same as in the third phase, with a little twist in them and somewhat similar findings. (Wamba et al., \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) studied Big Data Analytics Capability (BDAC) grounded in the resource-based view and incorporating insights from the literature on big data analytics (BDA), information system (IS) success, and the business value of information technology (IT). The findings support the conceptualization of the hierarchical BDAC model, demonstrating both direct and indirect impacts on FPER. Moreover, the results underscore the substantial mediating role of PODC, offering valuable insights and contributing to enhanced firm performance. The study concludes by outlining practical and research implications. (Rajapathirana and Hui, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) discussed innovation, and the findings of the study suggest that the effective management of innovation capability can lead to more impactful innovation outcomes, thereby enhancing overall performance and providing managerial benefits for insurance companies and (Cai and Li, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) studied eco-innovation, the results of the study indicated that specific factors, such as technological capabilities, environmental, organizational capabilities, market-based instruments, competitive pressures, and customer green demand, contribute to the adoption of eco-innovation. The findings of (Tang et al., \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) indicate that green process innovation and green product innovation significantly and positively predict firm performance when not considering managerial concern for the environment. However, once managerial concern is taken into account, it was observed that it enhances the positive effect of green process innovation on firm performance. On the other hand, green product innovation no longer explains significant unique variances in firms\u0026rsquo; performance. (Ben Arfi, Hikkerova and Sahut, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) studied the dynamics between internal and external knowledge sharing in the context of green innovation and assesses its impact on organizational performance. The empirical findings reveal that various types of external knowledge do not yield equivalent outcomes in terms of green innovation. Additionally, the success of the innovation process is significantly influenced by the access to knowledge sources, particularly the integration of internal and external knowledge at each stage of the green innovation process. The success of green innovations reflects the organizational absorptive capacity of external knowledge and its conversion into internal skills. However, it is acknowledged that risks associated with knowledge transfer can potentially hinder the positive relationship between green innovation and firms' performance, leading to the financial failure of green innovations. During this time, environmental concerns have also emerged as the priority of researchers pursuing their research in the area of technology as an enabler to entrepreneurial performance. It resulted in research studies focusing on eco-innovation, green innovation and their implications on firm performance, which is evident from the top-cited research studies published during 2017\u0026ndash;2020 and 2021\u0026ndash;2023.\u003c/p\u003e \u003cp\u003eResearch evidenced the significant and positive impact of green product and process innovations on the firm performance. However, this impact is influenced by the firm\u0026rsquo;s access to internal and external knowledge sources. Top-cited research published during 2021\u0026ndash;2023 has also focused their attention on emerging technology areas like artificial intelligence, and social media, etc. and their contribution towards the organizational performance. Research found that how an organization\u0026rsquo;s ability to quickly adapt with the technology changes of the time like building artificial intelligence capability, using social media, and innovating their business models can heavily impact their performance. During this phase, (Mikalef and Gupta, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) proposed a theoretical framework incorporating Artificial intelligence (AI) and its capability with organizational creativity and enhanced performance. The empirical results validate the proposed theoretical framework and corresponding instrument, confirming that an AI capability is associated with increased organizational creativity and enhanced performance. (Tajvidi and Karami, \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) introduced a novel perspective on the impact of social media usage in Small and Medium-sized Enterprises (SMEs). The results reveal a positive and significant relationship between social media usage and firm performance. Furthermore, the findings emphasize that marketing capabilities, particularly in branding and innovation, play a positive and significant mediating role in the connection between social media usage and firm performance. (Gu, Yang and Huo, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) investigated the cultivation of supply chain (SC) resilience and its potential positive impact on firm performance and the delivery of customer value are subjects of uncertainty. The results suggest that both supplier and customer resilience can enhance SC performance, with only explorative use of IT with suppliers and customers showing significant effects. Additionally, ambidextrous use of IT on the customer side is found to be effective, and the exploitative and explorative use of IT complements each other in improving customer resilience. These findings contribute to the literature on both IT and SC resilience. (Singh et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) delves into the direct and indirect relationships among stakeholder pressure, green dynamic capabilities, green innovation, and the performance of small and medium-sized enterprises (SMEs) in emerging markets. The results reveal that stakeholder pressure influences green dynamic capability, which, in turn, affects green innovation and ultimately influences firm performance. Furthermore, the findings suggest that green dynamic capability mediates the influence of stakeholder pressure on green innovation, and green innovation mediates the impact of green dynamic capability on firm performance. The study's outcomes carry significant implications for both theoretical understanding and practical applications. (Clauss et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) focused on the organizational antecedents of business model innovations (BMIs). The results indicate a positive relationship between strategic agility and BMI, strengthened by the degree of environmental turbulence. Furthermore, while value proposition and value creation BMIs are positively related to firm performance, value capture innovation shows a negative relationship with firm performance, contrary to predictions. The findings also suggest that BMI is an important intermediary mechanism through which a firm's strategic agility contributes to superior performance.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe current study has performed performance analysis technique in bibliometric analysis to understand the publication pattern of research studies and identify the most cited authors, research studies, most impactful journals, institutions, and countries studying the role of technology as an enabler to the entrepreneurial performance. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e reflects that how authors\u0026rsquo; inclinations towards studying the impact of technology-related interventions on the performance of entrepreneurial ventures has increased over the period of time. Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e to \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e represents the various performance metrics for the research studies taken into this study and offer meaningful understanding about top cited research studies of this domain along with increasing awareness about various authors, countries, and institutions offering their meaningful contribution to this area of research inquiry.\u003c/p\u003e \u003cp\u003eThe current study also uses the co-word analysis using author keywords in bibliometric analysis to identify the emerging themes from the research studies published during different timelines, taken into this research study. Content analysis section of this research study summarizes the findings from each emerging theme during different timelines. Looking at these themes, it can inferred that while the research studies during the initial period (1977\u0026ndash;1999) focused on basic aspects of investment in technology and how this investment is leading towards changing the business strategies to further result in impacting the firm performance, research studies during later periods focused on more mature aspects of technology interventions like technology capability, innovation capability, types of innovations, environmental aspects of innovation, application of technology into supply chain, etc. along with the specific emerging technology-based application like social media, artificial intelligence, big data analytics, blockchain etc. and their implications on various aspects of entrepreneurial performance. Firm performance and innovation, Organizational performance and innovation emerged as the central theme during 2000\u0026ndash;2010 and 2011\u0026ndash;2016. However, the focus of research during 2000\u0026ndash;2010 was also on research and development intensity, firm\u0026rsquo;s ability to utilize their knowledge resources, and building an organizational culture of innovation to further impact the organizational performance. Research studies during 2011\u0026ndash;2016 also focused on market orientation aspects of the firm, implications of technology into enabling supply chain integration, knowledge sharing, and open innovation and their relationship with the various aspects of firm performance. Research studies during 2017\u0026ndash;2020 and 2021\u0026ndash;2023 focused on the most recent technological interventions like emergence of social media, artificial intelligence, big data, blockchain, etc. and their impact on entrepreneurial performance. The development of AI from conceptual algorithms to tangible business solutions is noteworthy. Sectors from e-commerce to healthcare have been transformed through machine learning models, predictive analytics, and automation tools (Brynjolfsson and Mcafee, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The transition was not solely focused on improving efficiency; rather, it was characterized by a push towards personalization and the adoption of real-time solutions. Start-ups embraced AI to optimize supply chains, elevate customer experiences, and guide strategic decision-making (Chibuike Daraojimba et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). They also researched about how various technological interventions are helping firms with improving their performance and sustainable development.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe current study also utilizes the top-cited research studies from each theme to look at the pattern of theoretical foundations, regions studied and statistical methods used while measuring and analyzing the relationships between various aspects of technological interventions and entrepreneurial performance through empirical research. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the key theories, regions studied, and methodology used in research studies linking technology and entrepreneurial performance since 1977. Most research studies have utilized the resource-based view, knowledge-based view, game theory, contingency theory, innovation-diffusion theory, and technology-organization-environment (TOE) theory as theoretical foundations to build their research frameworks and test the relationship among the constructs relevant to their studies linking technology and entrepreneurial performance. Structural equation modelling and regression analysis were commonly applied as statistical methodology in most of the research studies to analyze the collected data. While majority of the empirical research linking technology and entrepreneurial performance was performed covering different nations of Europe, a significant amount of research studies has also been performed in the national contexts of USA and China. In Europe itself, Spain was the most studied nation by the researchers and scholars in terms of performing empirical research linking technology and entrepreneurial performance. In most of the research studies, firm performance has been measured as a multi-item scale covering both financial and non-financial aspects of an entrepreneurial organization.\u003c/p\u003e \u003cp\u003eLooking at the research combining all the timelines taken into this study, the investment in information technology and using technology-based emerging applications like social media cannot always ensure the improvement in the firm performance. It is the firm\u0026rsquo;s ability to channelize the technology-based efforts in a direction to reap the best benefits out of them. Research evidenced that while application of social media cannot guarantee and result in direct improvement in the firm performance, it can help the small and medium-sized enterprises (SMEs) leverage the social media to connect better with their stakeholders.\u003c/p\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003eContribution, Limitation, and Future Scope\u003c/h2\u003e \u003cp\u003eThis research study contributes to the entrepreneurship literature by exploring the different dimensions of the empirical research like common themes, constructs, and theoretical foundations linking empirical research on technology and entrepreneurial performance. This will further encourage the researchers and scholars in this field to deepen their understanding of this domain and take insights for future research studies. The novelty of this research study is in its approach to reviewing the empirical literature linking technology and entrepreneurial performance, which is a grey area for this domain of research study. Another novelty of this research study is in reviewing the literature in a systematic and phase-wise manner and offering critical insights by mapping the literature across various timelines.\u003c/p\u003e \u003cp\u003eHowever, there are two intrinsic limitations to the results of this study. First, the sample under analysis comprises of research studies only in English-language and from the journals that are indexed in the Scopus database as well as having a rating in ABDC rating of journals. Further, only those research studies have been taken into the current study, that has received at least one citation, with an exemption to the recent research studies published in 2023. Subsequent research endeavors could broaden the scope of the document search to encompass journals from diverse databases and ratings, as well as books, book chapters, conference proceedings, and documents published in many languages. They can also include the research studies having no citations. Second, a wider range of previously published empirical research linking technology and entrepreneurial performance is captured by the search phrase used for database exploration. Future studies, however, might try to organize the literature linking technology and entrepreneurial performance with a more focused approach.\u003c/p\u003e \u003c/div\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbebe, M. (2014) \u0026lsquo;Electronic commerce adoption, entrepreneurial orientation and small- and medium-sized enterprise (SME) performance\u0026rsquo;, Journal of Small Business and Enterprise Development, 21(1), pp. 100\u0026ndash;116. 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(2009) \u0026lsquo;A typology of social entrepreneurs: Motives, search processes and ethical challenges\u0026rsquo;, Journal of Business Venturing, 24(5), pp. 519\u0026ndash;532. Available at: https://doi.org/10.1016/j.jbusvent.2008.04.007.\u003c/li\u003e\n\u003cli\u003eZahra, S.A. and Covin, J.G. (1993) \u0026lsquo;Business strategy, technology policy and firm performance\u0026rsquo;, Strategic Management Journal, 14(6), pp. 451\u0026ndash;478. Available at: https://doi.org/10.1002/smj.4250140605.\u003c/li\u003e\n\u003cli\u003eZhao, H., Seibert, S.E. and Lumpkin, G.T. (2010) \u0026lsquo;The relationship of personality to entrepreneurial intentions and performance: A meta-analytic review\u0026rsquo;, Journal of Management, pp. 381\u0026ndash;404. Available at: https://doi.org/10.1177/0149206309335187.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Footnotes","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e This resulted in the display of 4631 research studies on the search page. Nevertheless, the Scopus database restricted authors from retrieving bibliometric details for search results, capping the limit at 2000 results. The timelines to download these search results were decided based on the author's understanding so that all the search results could be downloaded and utilized further for the analysis.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Entrepreneurship Development Institute of India","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"bibliometric analysis, entrepreneurial performance, innovation, literature review, technology","lastPublishedDoi":"10.21203/rs.3.rs-8631639/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8631639/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eEntrepreneurial performance is a well-known concept in the domain of entrepreneurship. While the previous research in this area has linked entrepreneurial performance to a number of factors, including personality traits, entrepreneurial orientation, firm strategy, networking ability, and many more, recent literature has drawn significant attention to the impact of technology adoption, innovation capability, and related variables on the performance of entrepreneurial ventures. Therefore, we conducted a systematic literature review employing the bibliometric methodology to identify the key research areas and directions of earlier quantitative research linking technology and entrepreneurial performance. The research findings indicate that it is not always that technology adoption will lead to better firm performance. Therefore, it also emphasizes the importance of identifying the required characteristics of the firms and supporting actors and determining the optimal timing for technology adoption, which may lead to better firm performance. The findings also revealed the major theories, methodologies used, and regions studied in this domain area of research since 1977.\u003c/p\u003e","manuscriptTitle":"Technology as an Enabler to Entrepreneurial Performance: Evidence from Past Literature of Quantitative Research","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-21 06:58:35","doi":"10.21203/rs.3.rs-8631639/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4a7b1ee4-a50d-4296-827e-114d04e21ea0","owner":[],"postedDate":"January 21st, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":61318073,"name":"Entrepreneurship"},{"id":61318074,"name":"Management"}],"tags":[],"updatedAt":"2026-01-21T06:58:35+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-21 06:58:35","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8631639","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8631639","identity":"rs-8631639","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}