Knowledge Management in Software Development Outsourcing: A systematic literature review

Knowledge Management in Software Development Outsourcing: A systematic literature review | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 22 January 2025 V1 Latest version Share on Knowledge Management in Software Development Outsourcing: A systematic literature review Author : Solomon Abebe Nurye 0009-0000-8734-0021 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.173753920.05335516/v1 344 views 223 downloads Contents Abstract Introduction Background Methods Data extraction and synthesis Results Limitations of existing studies and future research directions One-directional flow of Knowledge The interchangeable use of conceptually different knowledge management processes Mutual SDO success draws less attention Conclusion Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Knowledge management is widely recognized as a means of improving software development outsourcing (SDO) success due to the high failure rate and knowledge-intensive nature of SDO projects. However, how knowledge is effectively managed in SDO arrangements remains a challenge. This study aims to systematically review knowledge management studies linked with SDO success and analyze 32 research articles published in peer-reviewed journals from 2001 to 2023. Furthermore, the study strives to uncover gaps and research opportunities in SDO from the perspective of knowledge management. The main findings of this study reveal that knowledge categories in SDO are based on traditional tacit and explicit dichotomies, and an outsourcing partner does not have the full range of knowledge needed for developing the software. Most studies show one-way knowledge flow, with knowledge transfer being the most researched knowledge management process. Additionally, the vendors’ perspective of SDO success is the most researched (47%), followed by clients’ (36%), and client-vendor (17%) perspectives, respectively. Furthermore, data collection from vendors and clients is primarily sourced from senior and middle-level business and IT/IS managers, while project managers are the primary focus from the client-vendor perspective. The study also demonstrates the specific knowledge items needed in the SDO context, the modes of knowledge flows, the key knowledge management processes, and SDO success dimensions from the perspectives of clients, vendors, and both. Then, it develops a holistic knowledge management-based SDO success framework. It suggests ample avenues for future research to improve SDO success from the perspective of knowledge management. Introduction Software development outsourcing (SDO) is a viable business strategy for most modern organizations. However, ensuring its success and adding value to an outsourcing party is challenging (Fehrenbacher and Wiener, 2019). SDO is a business practice where a client (i.e., service receiver) contracts out all or a portion of its software development activities to a vendor (i.e., service provider) within a predetermined time frame, regardless of the vendor’s location (Khan et al. 2011). Outsourcing partners engage in such contractual relationships to achieve economies of scale, gain access to new knowledge and capabilities, improve service quality, and reduce operational costs while gaining business value (Wang and Wang, 2019; Bui et al., 2019). Despite the pervasiveness of SDO, many outsourcing deals have been reported as unsuccessful (Wolverton et al., 2020; Wang et al., 2018). They are characterized by failure to: work within the allotted budget (Konning et al., 2021); achieve clients’ expected benefits (Wolverton et al., 2020); meet their goals, schedule, and performance standards (Khan and Khan, 2017; Ulhas et al., 2016). This anecdotal evidence shows that SDO success and delivering business values from outsourcing deals remain challenging for business managers. Thus, further study is demanding to enhance SDO performance (Mazumder and Garg, 2021; Al-Emran et al., 2018). SDO is a complex and knowledge-intensive activity involving the effective transfer, acquisition, creation, and utilization of specialized knowledge to guide designs and develop the new software system (Rosin et al., 2019; Kammani, 2013). As a result, it is necessary to investigate the connection between knowledge management (KM) and SDO success (Mazumder and Garg, 2021; Al-Emran et al., 2018). KM is concerned with transferring, integrating, creating, and applying the knowledge that is available within outsourcing partners to achieve a common goal (Bernard and Tichkiewitch, 2008). To effectively manage knowledge during outsourced software development projects, a holistic knowledge management framework is required. A more comprehensive framework can lead to improved SDO performance as it provides a bigger picture of the specific knowledge items required, the modes of knowledge flows, and the key knowledge management processes. More specifically, it is crucial to properly identify and understand the unique characteristics of each piece of knowledge involved in the SDO context to maximize its transferability, storage, and application (Kulkarni and Freeze, 2011). Besides, more emphasis needs to be given to the modes of knowledge flow during outsourced software development projects. In SDO arrangements, knowledge flows in two ways (Smuts et al., 2017; Liang et al., 2016): the client becomes a recipient of the vendor’s knowledge transfer, and vice versa. An outsourcing partner assumes both knowledge source and knowledge receiver responsibilities. The proper management of a two-way knowledge flow can increase both the knowledge pool and the chances of successful utilization of knowledge (Teo and Bhattacherjee, 2014; Wang and Gan, 2010). Although different types of knowledge might be available, the knowledge-related practices of an outsourcing partner have an impact on the effective management of knowledge. Most review articles show the antecedents and effects of knowledge sharing on SDO success (Ali et al., 2017; Zahedi et al., 2016). Although each review provides a valuable synthesis of knowledge management within the context of SDO, further examination is required due to the high failure rate of SDO projects (Konning et al., 2021; Wolverton et al., 2020). As shown in Table 1, most research is based on the one-way traditional knowledge flow model, where technical knowledge is mostly transferred from the vendor to the client (Zahedi et al., 2016; Strasser and Westner, 2015). Thus, a broader understanding of the requisite knowledge in the two-way flow of knowledge is highly important to successfully managing knowledge. In addition, most published surveys have shown only a single process or dimension of knowledge management, i.e., knowledge sharing (Anwar et al., 2019; Könning et al., 2019). While knowledge management is a broad concept that includes different processes and activities to solve problems arising from outsourced software development projects (Deng and Mao, 2012), only knowledge-sharing activity does not necessarily lead to SDO success (Alavi and Leidner, 2001). Knowledge management produces better performance when knowledge is effectively created, shared, stored, and applied (Noh et al., 2016). A deeper understanding of knowledge management processes is thus necessary to improve software development processes and outcomes (Teo and Bhattacherjee, 2014; Lertpittayapoom, 2007). While some summarized works are based on the generic knowledge taxonomies (Zahedi et al., 2016; Strasser and Westner, 2015), others fail to mention the knowledge categories (Anwar et al., 2019; Al-Emran et al., 2018). It would be challenging for outsourcing partners to determine in advance the potential knowledge resources needed for SDO based on the traditional explicit or tacit categories of knowledge (Santhanam et al., 2007). Thus, it is essential to recognize the many kinds of knowledge that are involved in software development activity in order to better manage knowledge throughout the process (Holsapple and Joshi, 2004). Therefore, further research is required to fully characterize SDO context specific knowledge. A careful examination of the literature reveals that there are limited systematic reviews that intend to improve SDO success from the perspective of knowledge management. Thus, this study is the first to address the gap in the literature by explicitly examining the specific knowledge items, the two-way knowledge flows, the key knowledge management processes needed to improve SDO success, and the dimensions of success from the perspectives of client, vendor, and both client and vendor. Certainly! Apologies for the previous omissions. Below is the complete LaTeX document that includes all the requested sections, arguments, code snippets, and proofs, organized logically into a single cohesive document. “‘latex Table 1 Published surveys review knowledge management in SDO studies. Zahedi et al. (2019) 2000-2014 61 One Generic One-way No Focused on the offshore SDO knowledge sharing challenges and practices, identified generic knowledge types in SDO (i.e., tacit and explicit), and traditional one-way knowledge flow Anwar et al. (2019) 2010-2017 42 One No Two-way No Focused on the offshore SDO model, a single dimension of KM (i.e., knowledge sharing), and identified generic knowledge types in SDO (i.e., tacit and explicit) Al-Emran (2018) 2001-2018 41 Three Generic One-way No Focused on specific (business and technical) and generic knowledge types (i.e., tacit and explicit). A brief discussion of three KM processes Ali et al. (2017) 2001-2016 152 One No No No Focused on the analysis of recent developments in ITO research. Attempting to discuss a single activity of knowledge management (i.e., knowledge sharing) Konning et al. (2019) 2015–2017 63 One No One-way No Focused on determinants of IT sourcing outcomes and a single activity of knowledge management Strasser and Westner (2015) 1999–2009 95 Two Generic One-way No Highlighted the role of knowledge sharing in offshore software development project success Ali et al. (2018) 2002–2015 75 One No No No Focused on global software development organizations. A brief discussion of two dimensions of knowledge management This study 2001–2023 32 More than three Specific Two-way Yes Review of knowledge management models of SDO success; recommend future research direction in the area To mention the key contributions, this research: • identifies knowledge management practices in the SDO context. This creates our understanding of which knowledge management processes are widely implemented and which are less. • underscores the criticality of the two-way knowledge flow during the course of outsourced software development projects to maximize knowledge creation, storage, and application. • makes a conceptual distinction between knowledge transfer and knowledge sharing, although the two concepts are interchangeably used at the inter-organizational level in prior SDO studies. • highlights the mutuality of SDO success by examining it from the perspective of both clients and vendors. This can lead to increased value outcomes for both parties involved in SDO deals. • identifies and broadens our understanding of the specific knowledge types in the SDO arrangements. • develops a knowledge management-based SDO framework that can serve as a guide to effectively managing knowledge and increasing SDO success. • highlights limitations and provides future research directions for improving SDO success from knowledge management perspectives. The remainder of this review is structured as follows: Section 2 presents the background, knowledge management in SDO context. Section 3 describes the research method adopted to select and review the literature needed for this research and presents the chosen framework for analysis. Section 4 presents the results of the systematic review. Section 5 deals with the discussion, including the limitations of existing studies and suggestions for future research directions. Finally, Section 6 concludes this review with a summary of the key findings drawn from the survey. Background This section provides a brief background on knowledge and knowledge management in general and the SDO context in particular. Knowledge and Knowledge Management Various definitions of knowledge and knowledge management can be found in the knowledge management literature. Davenport and Prusak (1998) define knowledge as a combination of contextual information, expert insight, framed experience, and values that serve as the foundation for meaningful action and thought. Although scholarly literature offers various classifications of knowledge (Alavi and Leidner, 2001; Lam, 2000), explicit and tacit distinctions are widely acknowledged (Nidhra et al., 2013). Explicit knowledge can be codified and transferred easily in formal language (Nonaka, 1994). Conversely, tacit knowledge is based on experiences, actions, and engagement in specific contexts (Alavi and Leidner, 2001). Normally, tacit knowledge is difficult to communicate, formalize, and codify (Khamseh and Jolly, 2008). In conclusion, the majority of knowledge taxonomies described in the literature are general, higher-level classifications. As a result, successful knowledge management within the context of SDO requires a detailed understanding of the specific knowledge types involved in such knowledge work. Generally, knowledge management refers to the purposeful, organized, and systematic process of creating, transferring, storing, applying, and updating knowledge in order to achieve superior organizational outcomes, such as the creation of innovative products and services, gaining competitive advantages, and providing services at a reasonable cost (Bernard and Tichkiewitch, 2008). Several components of knowledge management have been identified by researchers (Shih and Tsai, 2016; Lee et al., 2016). Table 2 lists the key knowledge management processes based on existing literature. Knowledge Management in SDO Context In the context of SDO, there are two primary types of knowledge, namely business knowledge and technical knowledge (Hamid and Salim, 2011; Gopal and Gosain, 2010). Knowledge about the client’s long-term strategy, business processes, rules, and needs that the new software system must meet is referred to as business knowledge (Chang and Parikh, 2006). Technical knowledge describes the knowledge that converts a client’s business needs and requirements into a software-based solution (Tiwana et al., 2003). This knowledge includes software system development procedures, programming languages, and tools (Xu and Ma, 2008). Thus, understanding and effective management of the different types of knowledge during the software development process is critical to successful SDO deals (Deng and Mao, 2012; Hamid and Salim, 2011). Certainly! Apologies for the previous omissions. Below is the complete LaTeX document that includes all the requested sections, arguments, code snippets, and proofs, organized logically into a single cohesive document. “‘latex Table 2 Conceptual definitions of knowledge management processes. Knowledge Transfer Involves a bi-directional flow of knowledge between outsourcing partners during SDO project undertakings Teo and Bhattacherjee (2014) Knowledge Creation The continual improvement and creation of new knowledge by expanding the existing knowledge base Takeuchi and Nonaka (2000) Knowledge Dissemination The ability of a knowledge source to codify, articulate, and communicate the required knowledge to a recipient Mu et al. (2010) Knowledge Absorption The ability of a knowledge recipient to recognize the value, assimilate, transform, and exploit new external knowledge for SDO tasks Cohen and Levinthal (1990), Ko et al. (2005) Knowledge Storage The ability of a firm to organize, structure, and store technical and project related knowledge for immediate and future use Shih and Tsai (2016) Knowledge Application The ability of a knowledge recipient to use existing and transferred knowledge to accomplish SDO tasks and improve its internal business operations Teo and Bhattacherjee (2014) Certainly! Apologies for the previous omissions. Below is the complete LaTeX document that includes all the requested sections, arguments, code snippets, and proofs, organized logically into a single cohesive document. “‘latex Certainly! Apologies for the previous omissions. Below is the complete LaTeX document that includes all the requested sections, arguments, code snippets, and proofs, organized logically into a single cohesive document. “‘latex Methods In order to collect evidence from the existing empirical studies, this study used the systematic literature review method. This method has a high scientific value because of its well-formulated research questions, unbiased selection and analysis of relevant studies, and evaluation of a study’s quality based on the criteria set (Al-Emran et al., 2018; Bjørnson and Dingsøyr, 2008). This study systematically reviews selected literature that focuses on knowledge management in the SDO context, based on the recommendations set forth by (Keele, 2007). Besides, it takes into account the procedures followed in other related systematic reviews (Anwar et al., 2019; Al-Emran et al., 2018). In conducting the review, three main phases are followed: defining a review protocol, conducting the review, and reporting the review. The review protocol comprises these elements: (i) developing research questions; (ii) identifying data sources and search strategies; (iii) defining inclusion and exclusion criteria; (iv) study selection; (v) conducting quality assessment; and (vi) data extraction and synthesis. The details of these phases are given below. Research questions The purpose of this study is to systematically review empirical research that links knowledge management with SDO success. Going forward, the following research questions are formulated: 1. What are the SDO context-specific knowledge types in the onshore and offshore outsourcing models as reported in the existing literature? 2. Which type of knowledge does an outsourcing partner own and lack? 3. What is the mode of knowledge flow between outsourcing partners (one or two-directional)? 4. Which knowledge management processes are studied considering their relationship with SDO success, and how are these studies distributed across countries? 5. What are the dimensions of SDO success, and what are the types of participants in the collected studies? Data sources and search strategies Literature compilation was done in January 2024 by querying the different digital databases with search keywords that are closely related to the area under study. The databases include Web of Science, Emerald, IEEE, ScienceDirect, Taylor & Francis, ACM Digital Library, and Google Scholar. More specifically, the search keywords are ((“knowledge management”) OR (“knowledge sharing”) OR (“knowledge transfer”) OR (“knowledge application”) OR (“knowledge creation”) OR (“knowledge acquisition”)) AND ((“outsourcing success”) OR (“outsourcing performance”) OR (“software outsourcing”) OR (“IT outsourcing”)). Inclusion and exclusion criteria Inclusion criteria are used to select the relevant primary studies from the pool of literature retrieved based on the formulated search strategies. The resulting literature will be used as a source to extract data. The following are the requirements for inclusion: • Studies that link knowledge management with SDO, • Studies that deal with information system, information technology, or SDO success, • Studies that focus on knowledge management between the client and the vendor, • Studies that adopted empirical methods, such as surveys and case studies, • Studies that are written in the English language. Furthermore, the following exclusion criteria are defined: Studies that do not link knowledge management with software development, information systems, or information technology outsourcing, • Studies that focused on knowledge management processes or activities of the client’s team or between the vendor’s team, Studies that are in any other language than English. Study selection The initial search using the keywords and search terms formulated in Section 3.2 resulted in 298 articles. Then, 78 duplicates were removed. The remaining 220 articles were screened based on the defined inclusion and exclusion criteria. Accordingly, 32 research articles met the inclusion criteria. The search and refinement activities were carried out based on the principles of Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) (Moher et al., 2010). Figure 1 depicts the PRISMA flowchart. Quality assessment In addition to selecting relevant ones based on inclusion and exclusion criteria, assessing the quality of the articles is crucial (Al-Emran et al., 2018). The quality assessment checklist that follows is employed to ensure the quality of the selected research articles (N = 32): Does the study describe the impact of knowledge management on SDO success? Certainly! Apologies for the previous omissions. Below is the complete LaTeX document that includes all the requested sections, arguments, code snippets, and proofs, organized logically into a single cohesive document. “‘latex Fig, 1. PRISMA flowchart for the selected studies. Does the study empirically test the impact of knowledge management on SDO success? Each of the above questions was marked as ‘YES’, ‘NO’, or ‘NA’. All the selected studies fulfil this quality assessment, which indicates that these articles qualify for the subsequent analysis. Data extraction and synthesis This section presents how data are extracted from the selected articles and analysed to address the five research questions. Data extraction The data extraction stage involves collecting data, which aids in answering the research questions. The relevant data items extracted from each research article are carefully documented in a spreadsheet for subsequent analysis. Synthesis Both quantitative and qualitative data are extracted from the selected 32 articles. First, a quantitative data analysis technique was employed to synthesize the extracted data, and the descriptive results are presented in Section 4. Second, the qualitative data were analysed using a thematic analysis technique (Boyatzis, 1998), which enables researchers to analyse relevant data based on specific questions (Braun and Clarke, 2006). The results of this analysis, where the coding and analysis are facilitated through MS Excel, are reported in Section 4. Results In this section, the findings of the systematic review of 32 research articles published between 2001 and 2023 are reported. While the articles focus on knowledge management within the SDO context, the findings reported subsequently are based on the five research questions as follows: The first research question investigates the SDO context-specific knowledge types reported in the existing literature. As shown in Table 3, knowledge categories in the SDO context are based on the generic tacit and explicit dichotomies (14 studies) used in the knowledge management literature. Only four of the fourteen studies offered the specific knowledge items that fell into these knowledge categories. Accordingly, tacit knowledge includes people skills, insights, relevant experiences, and motivation; know-how (such as interpretations of cause-and-effect relationships); cultural norms, work routines, policies, and management practice. Explicit knowledge comprises system implementation procedures, documents collecting problems and solutions, system specifications, requirements documents, organizational structure diagrams, code, test scripts, and related metrics. The remaining ten studies provided more detailed categorizations of knowledge in the SDO setting, such as business application domain, technical, organizational, project management, and collective. Cultural knowledge is identified as another important knowledge type in offshore SDO deals. Five of the ten studies further classified technical and business knowledge, refer Table 3. As a result, stakeholder needs, business objectives for the software, business processes, and business rules comprise business application domain knowledge. Similarly, the technical knowledge consists of programming, software development techniques, estimating models, heuristics, best practices, software testing, and debugging techniques. On the other hand, the specific knowledge categories identified as being relevant to the SDO include technical knowledge, project management knowledge, business application domain knowledge, organizational knowledge, cultural knowledge, and collective knowledge (11 studies). Finally, of the total 32 studies, six did not indicate the required knowledge in SDO context. These studies focus on the conceptual discussions or roles of specific knowledge management processes in SDO. Without showing its difference or similarity with knowledge, information is typified as service schedules, service quality, production plans, and demand forecasts by one study (Navarro-Paule et al., 2023). The second research question investigates which type of knowledge an outsourcing partner owns and lacks. As a result, the results of the analysed studies demonstrate that clients possess rich business domain knowledge but lack technical knowledge. Similarly, vendors lack business domain knowledge, but they have rich technical knowledge. In addition, one of the studies indicates that mature clients have rich technical know-how in addition to their business knowledge (Huong et al., 2011). Overall, the findings demonstrate that each partner has specialized knowledge and that diverse knowledge and expertise need to be brought and applied throughout the software development process. The third research question is to determine if knowledge flows one way or two ways between outsourcing partners. Consequently, the studies’ findings demonstrate a one-way knowledge flow (21 studies) in which business knowledge flows from the client to the vendor (11 studies) and technical knowledge flows from the vendor to the client (ten studies). Additionally, eight studies documented a two-way flow of knowledge from the client to the vendor and vice versa. However, the knowledge flow mode was not revealed in two studies. One study also identifies the importance of bi-directional flows of information between outsourcing partners (Havarro-Paule et al., 2023). The knowledge flow modes in SDO are depicted in Figure 2. Fig. 2. Modes of Knowledge flow. Table 3 Types of knowledge in SDO context across the analysed studies. Teo and Bhattacherjee (2014) X X Blumenberg et al. (2009) X X Yang (2011) __ __ __ __ __ __ __ __ Prabhu et al. (2011) X X Zhang and Du (2011) X X Du et al. (2011) X Mathrani et al. (2012) X X Xu and Yao (2013) X X X Lee et al. (2008) X McGowan (2020) X X Deng and Mao (2012) X X X Khongmalai and Distanont (2022) X X Source Tacit Explicit Technical knowledge Business application domain knowledge Project Mgt’ knowledge Cultural knowledge Orgn’l knowledge Collective knowledge Faraji and Abdolvand (2016) __ __ __ __ __ __ __ __ Sharma et al. (2016) X X Liao et al. (2009) __ __ __ __ __ __ __ __ Lindberg et al. (2015) X Migdadi and Abu (2016) X X Betz et al. (2014) X Bustinza and Molina (2010) X X Lee (2001) X Westner and Strahringer (2010) X Wickramasinghe (2015) __ __ __ __ __ __ __ __ Williams (2011) X X Yun (2009) X X X Qian and Guo-Jie (2015) __ __ __ __ __ __ __ __ Thatcher et al. (2011) X X Tiwana (2004) X X Song et al. (2011) __ __ __ __ __ __ __ __ Ismail et al. (2005) X X Ai et al. (2012) X X X Huong et al (2011) X X Research question four analyses the studied knowledge management processes, considering their relationship with SDO success and the distribution of the studies across countries. Many studies were carried out to examine the effect of knowledge management processes on SDO success. To ascertain which knowledge management processes are most frequently examined, the processes are explicitly specified throughout the examined papers. Table 4 illustrates that knowledge transfer is the most frequently examined knowledge management process that has a positive impact on SDO success (14 studies). Other knowledge management processes studied are knowledge sharing (12 studies), knowledge application and integration (four studies), knowledge acquisition (two studies), knowledge creation, and knowledge retention (one study). However, two studies examined the effect of knowledge management on SDO success without showing a specific knowledge management process in their models. Source Knowledge Transfer Knowledge Sharing Knowledge creation Knowledge acquisition Knowledge integration Knowledge retention Knowledge application Frequency Teo and Bhattacherjee (2014), Blumenberg et al. (2009), Yang (2011), Mathrani et al. (2012), McGowan (2020), Deng and Mao (2012), Khongmalai and Distanont (2022), Faraji and Abdolvand (2016), Migdadi and Abu (2016), Betz et al. (2014), Westner and Strahringer (2010), Williams (2011), Yun (2009), Huong et al (2011) X 14 Prabhu et al. (2011), Zhang and Du (2011), Du et al. (2011), Xu and Yao (2013), Lee et al. (2008), Liao et al. (2009), Lindberg et al. (2015), Lee (2001), Wickramasinghe (2015), Song et al. (2011), Ismail et al. (2005), Ai et al. (2012) X 12 Migdadi and Abu (2016) X 1 Migdadi and Abu (2016) X 1 Yang (2011), Qian and Guo-Jie (2015) X 2 Qian and Guo-Jie (2015), Thatcher et al. (2011), Tiwana (2004) X 3 Yang (2011), Migdadi and Abu (2016), Williams (2011) X 3 Sharma et al. (2016), Bustinza and Molina (2010) 2 Figure 3 depicts the distribution of all the reviewed articles among the countries where these studies were carried out. As a result, China was the location of the majority of these investigations (eight studies). India and the USA follow this with four studies each, and Germany with three studies, respectively, among the other countries. Region-wise, the Asia-Pacific area leads with twenty, followed by Europe with five, North America with four, and West Asia with two. Nevertheless, research in South America and Africa has been scarce. Fig. 3. Distribution of studies by a country. Finally, research question five looks into the dimensions of SDO success and the types of participants. Accordingly, SDO success is multifaceted having diverse perceptions from stakeholders (Hughe, 2016). In the analysed studies, SDO success is examined from the perspectives of client, vendor, and client-vendor by involving different research participants. As reflected in Tables 5–7, the vendors’ perspective of success is the most researched (15 studies), followed by clients’ (12 studies) and client-vendor (five studies) perspectives, respectively. Concerning vendors, SDO success indicators include project delivery within time, cost, and quality; delivered financial benefits; and customer/client satisfaction. Project managers and senior and middle-level managers make up the majority of data gathering participants (see Table 5). Project managers view success mainly from the traditional technical aspects, namely, time, cost, and quality. Success indicators for senior and middle management include relationship quality, product quality, and an increased knowledge base. However, knowledge workers, such as software developers, who link success with creativity and innovation, have less participation. Table 5 Vendors’ perspective of SDO success. Yang (2011) Not mentioned Product innovation. Prabhu et al. (2011) Project managers Software quality (functionality, reliability, maintainability and usability) Zhang and Du (2011) Employees who involved in the outsourcing projects Satisfaction and business benefit Du et al. (2011) Knowledge workers Product success and personal satisfaction Mathrani et al. (2012) Senior and middle level managers Increased knowledge base Xu and Yao (2013) Executive Manager, director, project manager, software engineer Product quality and process efficiency Deng and Mao (2012) Project managers or team leaders Project quality and cost control Sharma et al. (2016) Top managers Relationship quality Wickramasinghe (2015) Software developers Innovation Williams (2011) Software engineers Gaining and applying knowledge for the benefit of client Yun (2009) Project director, senior service consultant, director of strategy and development department, and project manager, the team member of an offshore project Improving the productivity and quality of ISD project Qian and Guo-Jie (2015) Program managers and consulting experts Project quality and customer satisfaction Ai et al. (2012) Middle managers and knowledge workers Product success and personal satisfaction Huong et al (2011) Group leaders, project managers and team leaders Improved client-vendor relationship Song et al. (2011) Employees Not mentioned The client’s perspective on success includes realized benefits (strategic, economic, technological, individual, and organizational benefits); project completion within scope, time, cost, and quality; and overall satisfaction. In terms of participant types, Table 6 shows that most data from the client’s perspective is collected from senior and middle-level business managers and IT/IS managers. The business manager views enhanced operational and strategic performances as well as impacts at the individual, group, and organizational levels as key SDO success indicators. The IT/IS managers regard information quality, system quality, and strategic, economic, and technological benefits as dimensions of SDO success. However, the participation of end-users and project managers is low. One study by Navarro et al. Navarro-Paule et al. (2023) connected information sharing and outsourcing success. The study measures success as achievements of strategic, economic, and technological competence based on the perceptions of the clients’ functional managers. Table 6 Clients’ perspective of SDO success. Teo and Bhattacherjee (2014) Senior level IT executives (CIO or equivalent) Operational and strategic performances Blumenberg et al. (2009) Business managers Service quality Khongmalai and Distanont (2022) IT outsourcing staff Outsourcing’s efficiency and effectiveness, strategic benefit, economic benefit, and the overall satisfaction Faraji and Abdolvand (2016) Not mentioned Operational efficiency of the project Liao et al. (2009) MIS department managers Strategic, economic, and technological benefits Lindberg et al. (2015) IT Managers Strategic, economic, and technological benefits Migdadi and Abu (2016) Business and IT managers Individual impact, work group impact, organizational impact, information quality, system quality, vendor quality Betz et al. (2014) Project managers and business managers Not mentioned Bustinza and Molina (2010) CEOs Business benefits, organizational benefits Lee (2001) IS managers Strategic, economic, and technological benefits Westner and Strahringer (2010) CIOs, CEOs, and employees with non-management roles. Project time schedule, project budget, project functionality, project quality, and overall satisfaction Lastly, Table 7 shows SDO success from both the client and vendor perspectives. Accordingly, net benefits (strategic, economical, and technological benefits); service quality (reliability, responsiveness, and assurance); cost savings; and software development efficiencies and effectiveness are indicators of success. In the examined studies, project managers are the main subject of data gathering. Top managers and IT/IS executives from client-vendor firms, however, participate less. Table 7 Client-vendor perspective of SDO success. Thatcher et al. (2011) IT project managers Improved project outcomes and performance Tiwana (2004) Project managers Software design effectiveness, software development efficiency Ismail et al. (2005) IT managers Net benefits (strategic, economical, and technological benefits) and service quality (tangibles, reliability, responsiveness, and assurance) Lee et al. (2008) Top IT executives of client firms and representatives of vendor firms Strategic, economic and technological benefits McGowan (2020) Project managers, analysts, developers, subject matter experts, and other ITO knowledge workers. Increased organization’s intellectual capacity and cost-savings Certainly! Apologies for the previous omissions. Below is the complete LaTeX document that includes all the requested sections, arguments, code snippets, and proofs, organized logically into a single cohesive document. “‘latex Limitations of existing studies and future research directions The systematic literature review has revealed a growing interest in improving SDO success from the perspective of knowledge management over the years. Despite the recognized roles of knowledge management in SDO deals, the critical analysis unveiled several avenues for future research that are worth considering by the research community. Herein below, such limitations are listed; along with the potential research areas that can be addressed effectively in the future (refer to Figure 4 for a graphical summary): Different taxonomies of knowledge Table 3 lists the different categories of knowledge within the SDO context across the examined studies. The traditional tacit and explicit categories of knowledge are very generic and do not offer more detailed specifications of the knowledge items required in a particular knowledge work (Ein-Dor, 2011; Holsapple and Joshi, 2011). Generic knowledge taxonomies, while important, are insufficient to pre-establish the knowledge resources required for SDO (Santhanam et al., 2007). Successful knowledge management in knowledge-intensive work requires the identification of particular knowledge types (Holsapple and Joshi, 2004). As mentioned in Section 4, five studies provide comprehensive descriptions of the knowledge items that are needed for both technical and business knowledge. These comprise business domain knowledge, technical knowledge, software system application knowledge (such as structure, functionality, and use), software development methodology knowledge (such as development approaches, methods, techniques, and tools), organizational Fig. 4. A holistic knowledge management-based SDO success framework. knowledge (such as long-term strategy, constraints, and market challenges), and newly generated project-specific knowledge (such as requirements specifications, architectural models, and test plans). However, while business knowledge is both tacit (know-how regarding business processing) and explicit (such as documented routine work processes, standard rules of operating procedures, and requirements documents), less emphasis is placed on both dimensions of knowledge (Chang and Parikh, 2006). Additionally, there are explicit and tacit components to technical knowledge. Explicit components include written system specifications, systems design, test cases, data models, data flow diagrams, software codes, documentation, and manuals. Examples of tacit components include the know-how to normalize a database, the mental schemas of the new system, and the know-how of the technologies used. Consideration of these dimensions is important to maximize knowledge value and devise the appropriate mechanisms to transfer, store, and apply knowledge. In this regard, Wickramasinghe (2015) suggested that some knowledge management mechanisms are suitable for tacit knowledge but not for explicit knowledge. Thus, it is vital to pay heed to finer types of knowledge relevant to the OSD context (Santhanamet al., 2007). One-directional flow of Knowledge Figure 2 shows that one-way knowledge flows—from clients to vendors (35%) and from vendors to clients (32%)—account for 67% of the analysed studies. Conversely, 26% of the analysed studies show a two-way knowledge flow, from clients to vendors and vice versa. The dominant one-way knowledge flow mode has limitations in providing a complete picture of the key knowledge to be exchanged between outsourcing parties. While examining SDO success from the perspective of knowledge management, it is imperative to consider the two-way knowledge flows between outsourcing partners, the proper integration of the client’s business domain knowledge and the vendor’s technical knowledge, and the application of knowledge Holsapple, 2013; Tiwana, 2009). When the two-way knowledge flow is effectively managed during SDO engagement, the likelihood of SDO success can be increased. Therefore, antecedents of knowledge management (such as knowledge-based culture, structure, and technology of outsourcing partners) in a bi-directional flow of knowledge and their effects on SDO success are possible research areas to be considered. On top of that, SDO relationships are characterized by knowledge asymmetry, where a single party does not have the full range of knowledge (Voigt et al., 2007). The findings presented in Section 4 indicate that the requisite knowledge for developing the software exists in the client’s and vendor’s business environments. The outsourcing relationship provides a learning opportunity for outsourcing partners to gain and hone the knowledge and skills they lack (Teo and Bhattacherjee, 2014). On one hand, the client is supposed to learn the vendor’s technical expertise and best practices. On the other hand, the vendor needs to learn the client’s business processes, workflows, and existing systems and IT landscape. Thus, the achievement of learning in SDO deals can also be one avenue for future research. The interchangeable use of conceptually different knowledge management processes The main knowledge management processes in the analyzed studies are displayed in Table 4. As a result, knowledge transfer is the most frequently researched knowledge management process, followed by knowledge sharing, knowledge application and integration, knowledge acquisition, and knowledge creation and retention, respectively. These results are inconsistent with Al-Emran (2018), who noted that knowledge sharing is the most frequent knowledge management process studied. One possible explanation for this can be the terms knowledge sharing and knowledge transfer are often used interchangeably, although they differ in their focus and application (Hamid and Salim, 2011). Table 4 also shows this kind of discrepancy among the analyzed studies, specifically between knowledge sharing (39%) and transfer (45%). While knowledge transfer is more appropriate to be employed at the inter-organizational level, such as in SDO relationships, knowledge sharing can be used at the individual level of knowledge exchanges (Hamid and Salim, 2011). Knowledge transfer has a well-defined source and recipient and is goal-oriented and targeted (King and He, 2011). Thus, knowledge transfer is better chosen when referring to inter-organizational knowledge exchange, which is characterized by clearly defined objectives and the existence of a dedicated channel to facilitate knowledge flows. Moreover, in light of their connection to SDO, knowledge acquisition, creation, and retention have received less research attention. Thus, further research should focus on investigating the associations between these knowledge management processes and SDO success. Furthermore, the majority of the analyzed studies concentrated solely on knowledge transfer (14 studies), one aspect or process of knowledge management. It can be evident that the two separate concepts—knowledge application and knowledge transfer—are combined. Knowledge transfer does not mean knowledge application (Davenport and Prusak, 1998). While knowledge application refers to the extent to which the transferred knowledge is used for SDO tasks, knowledge transfer is the two-way flow of knowledge between outsourcing partners. Therefore, just transferring knowledge does not ensure that it will be applied to a particular activity. When used by the involved parties, the transferred knowledge can address the client’s business problems and increase SDO success (Teo and Bhattacherjee, 2014). What facilitates or hinders successful knowledge application in SDO relationships could be a potential area for future research. Mutual SDO success draws less attention Tables 5 to 7 indicate the analysed studies examined the relationship between knowledge management and SDO success from the vendors’ perspective (47%), clients’ perspective (36%) and client-vendor perspectives (17%). This shows that the client-vendor perspective of SDO success is less researched. As a result, researchers and practitioners in the area have gained little knowledge of outsourced software development projects’ success from both client and vendor perspectives. Thus, further research is needed to investigate the impact of knowledge management processes on mutual SDO success. In this regard, Mustak (2019) suggested that examining success from the perspective of both clients and vendors can lead to increased value outcomes for both parties. The mutuality of success is also underscored by (Mehta and Mehta, 2017), as the outsourcing trend has shifted to a partnership where the client and the vendor share their common goals and transfer each other’s knowledge to succeed in their SDO relationships. Besides, data need to be collected from a variety of participants, representing each party involved in the outsourcing relationship. By doing so, response bias can be minimized while determining SDO success through the lens of knowledge management. Conclusion This study aims to systematically review and synthesize prior research that connects knowledge management with SDO success. Therefore, this study enhances our understanding of the bi-directional flow of knowledge, the specific knowledge items within the SDO context, the key knowledge management processes that improve SDO success, and the criteria that are used to evaluate success from the perspectives of client, vendor, and client-vendor. Consequently, a holistic knowledge management-based SDO success framework has been proposed, serving as a guide to successfully manage knowledge and improve success. Drawing from the critical literature review, many directions for future research are also suggested to enhance SDO success from the perspective of knowledge management. Furthermore, this review study has implications for practice, as it highlights the need of two-way knowledge flows between outsourcing parties and informs outsourcing practitioners about the key knowledge management processes through which viable SDO success can be achieved. Information & Authors Information Version history V1 Version 1 22 January 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords knowledge management outsourcing software development success Authors Affiliations Solomon Abebe Nurye 0009-0000-8734-0021 [email protected] University of Gondar View all articles by this author Metrics & Citations Metrics Article Usage 344 views 223 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Solomon Abebe Nurye. Knowledge Management in Software Development Outsourcing: A systematic literature review. Authorea . 22 January 2025. 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