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Customer Knowledge Management in Enterprise Software Development Companies: Organizational, Human and Technological Perspective

Customer Knowledge Management in Enterprise Software Development Companies: Organizational, Human... In this study, Knowledge-Based View (KBV) and Theory of Technology in a Generic Customer Knowledge Manage- ment (CKM) Framework were assimilated to demonstrate the Organizational, Human and Technological anteced- ent factors that enable CKM processes to improve software product quality. A Theoretical CKM Framework was developed by extracting Human, Organizational and Technological factors from the literature, then, the “Tech- nique for Order of Preference by Similarity to Ideal Solution” (TOPSIS) Multi-Criteria Decision Making (MCDM) method was applied to find the importance level of factors to CKM development in software companies. The weight and priority of factors were determined by 31 experts in enterprise software development companies. The results show that, from an expert viewpoint, CKM antecedent factors are categorized into high priority and low priority groups. Organizational factors such as “Customer Involvement”, “Customer-Centric Culture” and “CKM Strategy Development” are high priority. Key words: qualimetry, knowledge management, enterprise software development, TOPSIS, summarizing indi- cator, multicriteria quality assessment, dimensionless scale INTRODUCTION and the overall success of the entire project [12, 15, 17, Product quality in organizations requires a long enhance- 18, 19]. Successful CKM in software companies improves ment process and mature business processes for product product quality. production [1, 2]. According to KBV, CKM are effective or- LITERATURE REVIEW ganizational factors that enhance software quality in soft- The rate of application of CKM in ES is low. For example, ware companies [3, 4]. Integrating Customer Knowledge according to an investigation of 22 software development (CK) in enterprise software development is still immature, companies that proposed their product in ELECOMP 2014 as it lacks a theoretical framework to fully capture CKM [5, (Big annual ICT exhibition in Tehran), 69% had no solution 6]. There are significant challenges regarding the transfer or guidelines for gathering customer knowledge. 81% of and integration of customer knowledge inside software them mentioned that the software production process in companies [7, 8, 9, 10]. A lack of senior management com- their companies is product centric rather than customer mitment to CKM, poor communication, a lack of cultural centric. There is a lack of systematic CKM processes in readiness, and a lack of customer management skills are many companies [5, 13, 20]. Ignoring the utilization of CK barriers to the design and implementation of CKM [9, 10, in several firms [21, 22, 23], an inadequate theoretical 11, 12]. Most major problems for the effective application framework for CKM antecedent factors and a lack of com- of CKM in many companies are organizational and not prehensive theoretical framework for CKM effects on technical [1, 2, 13, 14, 15, 16]. There is no doubt that ap- software quality in enterprise software development re- propriate communication and customer collaboration in flect a fundamental need for further exploration [1, 3, 9, different phases of Enterprise Software (ES) development 24, 25]. Most software companies in this study are Small project would help increase overall customer satisfaction © 2022 Author(s). This is an open access article licensed under the Creative Commons BY 4.0 (https://creativecommons.org/licenses/by/4.0/) 292 Management Systems in Production Engineering 2022, Volume 30, Issue 4 and Medium Enterprises (SMEs) [20, 24, 25, 26, 27, 28, 29, Taking these views into consideration, this study decided 30]. SMEs face resource constraints [1, 4, 6, 31]. Regard- to use 50 specialists for the data gathering stage. After dis- ing the high rate of failure in CKM projects [32, 33, 34, 35], tributing the survey questionnaire to 50 ES experts from determining important CKM success factors that decrease 13 different companies, 31 completed questionnaires the risk of failure is vital for managers and practitioners in were returned. software companies. The outcomes of this study help companies focus on high priority CKM factors and reduce TOPSIS Analysis organizational resource waste. Due to a history of poor In this study, we rank CKM success factors based on im- solutions coupled with technology failures, many compa- portance and relevance in ES development using TOPSIS. nies have a hard time justifying CKM initiatives [18, 23, 33, According to Cherniak, et al. [50], the TOPSIS procedure 36, 37, 38, 39, 40]. Understanding the antecedent weights has five steps. After forming an initial decision matrix, the helps software companies improve the success rate for procedure starts by normalizing the decision matrix. This CKM projects and motivate managers to implement CKM. is followed by building a weighted normalized decision Despite many studies that have examined CKM anteced- matrix in Step 2, determining the positive and negative ent factors in multiple contexts, none of them are com- ideal solutions in Step 3, and calculating separation prehensive enough to capture all factors into one single measures for each alternative in Step 4. The procedure framework. In this study, an empirical study was con- ends by computing the relative closeness coefficient. The ducted to investigate possible factors influencing CKM in set of alternatives (or candidates) is ranked according to ES development companies [41, 42]. The questions that the descending order of the closeness coefficient [51]. were asked in this study are: (a) What are the antecedent The procedure for the TOPSIS method consists of the fol- factors that affect CKM in an organization based on Hu- lowing steps: man, Organization and Technology frameworks? (b) What Given a set of alternatives, A = {A |i = 1, …, n} and a set of framework is appropriate to weigh and prioritize anteced- criteria, C = {C |i = 1, …, m}, ent factors using TOPSIS for ES development companies? where: 𝑋 = $𝑥& | 𝑖 = 1, ⋯ , 𝑛; 𝑗 = 1, ⋯ 𝑚1 denotes the set of !" GOAL OF THE WORK ratings and 𝑊 = $𝑤 5 | 𝑗 = 1, ⋯ , 𝑚1 is the set of weights. This paper evaluates the importance level of CKM critical Σ w = 1 = w + w + w + w + w = 0.066667 + 0.133333 + i 1 2 3 4 5 factors. This study proposes a framework to weigh and 0.2 + 0.266667 + 0.333333 = 1 prioritize CKM antecedent factors based on expert view- The first step of TOPSIS is to calculate normalized ratings points using TOPSIS in enterprise software development. by Eq. (1). Then we calculate the weighted normalized rat- ings by Eq. (2). OBJECTS AND METHODS OF RESEARCH #$ !" 𝑟̃ (𝑥) = , 𝑖 = 1, ⋯ , 𝑛; 𝑗 = 1, ⋯ , 𝑚 !" CKM Framework for the Software Companies (1) $ # %∑ #$ !%& !" This study investigates what of the extracted CKM ante- 𝑣0 (𝑥) = 𝑤 2 𝑟̃ (𝑥), 𝑖 = 1, ⋯ , 𝑛; 𝑗 = 1, ⋯ , 𝑚. (2) cedent factors [43] are suited for enterprise software de- !" " !" In the next step, the Positive Ideal Point (PIS) and the Neg- velopment companies. Appropriate techniques were cho- ative Ideal Point (NIS) are calculated (see Table 1) using sen to select suitable CKM antecedent factors for the Eq. (3). scope and purpose of this study. The TOPSIS method was ' ' ' ' ' used to choose appropriate factors and develop a frame- 8 𝑃𝐼𝑆 = 𝐴 = {𝑣0 (𝑥), 𝑣0 (𝑥), ⋯ , 𝑣0 (𝑥), ⋯ , 𝑣0 (𝑥)} ( ) * work for CKM for software development companies. = {(𝑚𝑎𝑥 𝑣0 (𝑥)|𝑗 ∈ 𝐽 ), (𝑚𝑖𝑛 𝑣0 (𝑥)|𝑗 ∈ 𝐽 )|𝑖 = !" ( !" ) ! ! 1, ⋯ , 𝑛} (3) Data Collection + + + + 𝑁𝐼𝑆 = 𝐴 = {𝑣0 (𝑥), 𝑣0 (𝑥), ⋯ , 𝑣0 (𝑥), ⋯ , 𝑣0 (𝑥)} ( ) " * After extracting the CKM impact factors, the priority and = {(𝑚𝑖𝑛 𝑣0 (𝑥)|𝑗 ∈ 𝐽 ), (𝑚𝑎𝑥 𝑣0 (𝑥)|𝑗 ∈ 𝐽 )|𝑖 = !" ( !" ) weight of the factors were used to select appropriate fac- ! ! 1, ⋯ , 𝑛} tors for ES development. This study consulted with ES de- where: velopment experts using a survey questionnaire designed J and J are the benefit and the cost attributes, respec- 1 2 to find out what extracted impact factors are most im- tively. portant for ES. The survey questionnaire included a list of CKM enablers and their definitions. This study asked ex- Table 1 perts to evaluate each factor using a 5-point Likert scale Positive Ideal Point (PIS) and the Negative Ideal Point (NIS) (not important, low important, important, moderate im- Max Vi1 Max Vi2 Max Vi3 Max Vi4 Max Vi5 portant, and very important). When it comes to MCDM 0.03306122 0.059446777 0.065833774 0.094859067 0.133627638 procedures, no guidelines exist for deciding the number Min Vi1 Min Vi2 Min Vi3 Min Vi4 Min Vi5 of respondents. As TOPSIS is not based on statistics, a 0 0 0.005486 0.007905 0 modest sample size was adequate [44, 45, 46]. In the opin- The following step is to calculate separation from PIS and ion of Dyadyura [47], MCDM such as TOPSIS and AHP (An- NIS by the alternatives. The separation values are meas- alytic Hierarchical Process) are scientifically applicable ured using a Euclidean distance given as: and do not require a large sample size. In the study con- ducted by Trishch, et al. [48, 49], MCDM procedures were ' * ' 𝑆 = ∑ [𝑣0 (𝑥) − 𝑣0 (𝑥)] , 𝑖 = 1, ⋯ , 𝑛 A (4) ! !" ",( " used to rank factors based on the viewpoint of 12 experts. A. KHOSRAVI et al. – Customer Knowledge Management in Enterprise Software Development… 293 The final ranking shows the overall viewpoint of 31 ex- + * + 𝑆 = ∑ [𝑣0 (𝑥) − 𝑣0 (𝑥)] , 𝑖 = 1, ⋯ , 𝑛 A (5) ! !" ",( " perts on the significance of each factor for enhancing CKM ' + in the enterprise software development domain. The 𝑚𝑎𝑥{ 𝑣0 (𝑥)} − 𝑣0 (𝑥) = 𝑚𝑖𝑛{ 𝑣0 (𝑥)} − 𝑣0 (𝑥) = 0. (6) !" " !" " overall viewpoint of the experts indicated that “Customer Accordingly, the similarities to PIS are calculated using Eq. Involvement” and “Customer-Centric Culture” have the (7). most significant effect on enhancing CKM in software .(0 ) ∗ ! 𝐶 = , 𝑖 = 1, ⋯ , 𝑛 (7) ! ( ' companies to achieve quality software. However, “Privacy [.(0 )'.(0 )] ! ! for customers” and “Intellectual Property” have a less sig- where: nificant effect on enhancing CKM in software companies. 𝐶 ∈ [0,1] ∀𝑖 = 1, ⋯ , 𝑛 (8) * It is clear from Table 2 that the distance between the rank Finally, the preferred orders are ranked according to C in of “Key Customer Management” and “Knowledge Map” is descending order. In Table 2 the ranks of 22 CKM factors considerable. The factor rankings before “Key Customer are presented. Management” are very near to each other (0.3 < Ranks > Table 2 0.4). Distance from positive and negative ideal Furthermore, the ranks of the factors after “Knowledge ' + ' + ∗ Factors 𝑫(𝑺 ) 𝑫(𝑺 ) 𝑫(𝑺 ) + 𝑫(𝑺 ) 𝑪 𝒊 𝒊 𝒊 𝒊 𝒊 Map” are very near each other as well (0.4 < Ranks > 0.6). Customer Thus, there is a breakpoint between the rank of these two 0.08272 0.120818 0.203538 0.59359 involvement factors (“Key Customer Management” and “Knowledge Customer-cen- 0.091899 0.132759 0.224658 0.590937 Map”) that can categorize the antecedent factors into two tric culture groups. The first group refers to high priority CKM ante- CKM Strategy 0.096197 0.138431 0.234628 0.590003 cedent factors (Rank > 0.5) and the second group refers to development low priority CKM antecedent factors (Rank < 0.4). 11 out Collaboration 0.086869 0.123678 0.210548 0.587413 of 22 factors are in the high priority CKM antecedent system Cross-func- group. This high priority group includes Organizational tional 0.086056 0.118937 0.204993 0.580199 factors (“Customer Involvement”, “Customer-Centric Cul- cooperation ture”, “CKM Strategy Development”, “Cross-Functional Individual Cooperation”, “Senior Management Support”, “Train- competences 0.092332 0.123465 0.215798 0.572135 ing”), Human factors (“Competencies and Skills”, “Trust and skills between customer and company”) and Technological fac- Trust tors (“CRM Technology Infrastructure”, “Collaboration between 0.084384 0.110967 0.19535 0.568038 System”, “Customer Knowledge Map”). The managers of customer software companies must give great attention to the suc- and company cessful implementation and deployment of CKM. This Top manager 0.088304 0.114491 0.202795 0.564566 study proposed a CKM framework for software compa- support CRM nies based on the highest priority CKM antecedent fac- technology 0.093538 0.118261 0.2118 0.558364 tors. infrastructure Training 0.087253 0.105486 0.192739 0.547299 DISCUSSION Knowledge After developing a theoretical framework based on 22 an- 0.094539 0.112504 0.207043 0.543385 map tecedent CKM factors extracted from the literature [52]. Key customer 0.123427 0.079196 0.202623 0.390853 The framework was evaluated by 31 experts in enterprise management software development in Iran. The TOPSIS method was Reward 0.123696 0.076964 0.20066 0.383553 used to rank the factors and it shows their significance for system enhancing CKM to improve software quality in software CK Oriented BP 0.128879 0.080094 0.208973 0.383275 development companies. Based on the result of the TOP- CK Quality 0.13581 0.081571 0.21738 0.375244 SIS analysis, some findings from previous studies were Individual 0.123018 0.071631 0.194649 0.368001 Motivation supported. Program cham- As discussed in the previous section, based on factor rank- 0.144845 0.075245 0.22009 0.341885 pion ings, the antecedent factors are classified into factors of Integrated high importance factors and factors of low importance. In knowledge Re- 0.130877 0.06798 0.198857 0.341851 the high importance group, the first three are Organiza- pository tional factors, which mean that Organizational CKM fac- Community 0.153343 0.077045 0.230388 0.334415 tors have more priority than Human and Technological of practice factors. CKM is based on people and social interaction, Social Media 0.147994 0.071706 0.2197 0.32638 where the organization is responsible for establishing the Provide right conditions for CKM, and information and communi- Privacy for cus- 0.137138 0.061561 0.198699 0.309822 cation technology helps to facilitate this [53]. This finding tomers Respect for was supported by the Theory of Technology. The results Intellectual 0.145573 0.065002 0.210576 0.308688 Property 294 Management Systems in Production Engineering 2022, Volume 30, Issue 4 of research work [54] noted that human actions are ena- This finding is in line with recent studies by [62] and [63], bled and constrained by organizations. However, the rules who identified that appropriate training is required to and the structures of organizations are the result of previ- make sure employees have enough IT skills and expertise ous actions. Technology is an instantiation of some of the to effectively absorb, share and utilize CK. The results of rules and resources constituting the structure of an organ- research work [64] noted that for successful CKM, three ization. Technology is created and changed by human ac- types of customer knowledge competencies are required: tion, yet it is also used by humans to accomplish actions. customer knowledge acquisition skills, customer Thus, it is clear from the results that for successful CKM knowledge sharing skills and customer knowledge use development, managers of software companies must fo- skills. The results of research work [65] highlighted the im- cus on organizational factors to enable the development portance of trust between customer and company for im- of other factors. proving the process of customer knowledge absorption. “Customer Involvement”, “Customer-Centric Culture” The results of research work [66] mentioned that one of and “CKM Strategy Development” were given a high pri- the key challenges in absorbing knowledge from custom- ority, and this confirms the result of works developed by ers in software development projects is a lack of trust be- [55, 56, 57]. Moreover, “Customer Privacy” and “Cus- tween customers and development teams. Organizational tomer’s Intellectual Property” have a lower priority and antecedent factors such as CKM strategy, top manage- experts consider these factors not very important for CKM ment support, and training are important for enhancing development. The results of research work [58] noted employees skills and providing a trusting environment that customers’ wishes, needs, and preferences influence [67]. the concept and design of a product or service. It was sug- The result of this study shows that from the 22 extracted gested that customers should be involved within the de- antecedent factors, 11 factors are in the highly important velopment phases of a product/service, which includes group based on 31 experts’ viewpoint in software devel- Idea Generation, Concept Development, Product Design, opment. Implementing and deploying CKM successfully in Prototyping/Testing, and Maintenance. At each different enterprise software development companies to improve stage, value is created collaboratively as organizations software quality strongly depends on these high priority gain insight into customer preferences and ideas based on factors. This finding is supported by the results of the re- continuous interaction and feedback from costumers [59, view [68], According to [69, 70], all of the antecedent fac- 60]. Important technological factors such as “collabora- tors in the high priority group have high iteration in the tion system”, “CRM Technology Infrastructure” and literature. In [71] shows that CKM was used in a variety of “Knowledge Map” facilitate absorbing, storing, organiz- contexts [72, 73, 74] provided evidence and supports our ing, and distributing customer knowledge. The knowledge findings, since all high priority factors were already used acquired is codified and stored in corporate databases in IT companies. This study’s findings are similar to past and knowledge warehouses. CRM Technology Infrastruc- findings, but this study is more comprehensive and con- ture helps companies to absorb and store all customer siders the entire CKM antecedent factors mentioned in transitions and provides a repository of feedback. previous studies. Some of the high frequency CKM ante- Knowledge Maps are used to organize explicit and tacit cedent factors in the literature were not selected in the knowledge and collaboration systems provides a collabo- high priority group because of the specific conditions of rative environment for sharing CK inside organizations software development in Iran. These factors may be more and between organizations and customers. significant in other countries or other contexts. “Customer-Centric Culture”, “Top Management Sup- ports” and “Training” are important organizational factors CONCLUSIONS that facilitate the absorption, sharing and utilization of The findings of this study build and expand CKM in enter- customer knowledge. The results of research work [61], prise software development companies. 22 factors were successful CKM requires the transformation of organiza- extracted from the CKM literature and categorized based tions from a product-centric focus to a customer centric on the Theory of Technology into Organizational, Human, focus. To provide a customer-centric culture that per- and Technological factors. According to the findings from ceives customers as a valuable source of knowledge, top the TOPSIS method, 11 factors from the extracted ante- management must inspire an organizational culture that cedent factors are in the highly important group based on motivates employees to acquire, share and use CK. Organ- the opinions of 31 software development expert. These izations need to change business processes and shape factors are critical for successfully implementing CKM. their organizational culture and routines to utilize the po- High priory organizational factors (“Customer Involve- tential of CRM systems to generate customer knowledge ment”, “Customer-Centric Culture”, “CKM Strategy Devel- and optimize benefits. Development of customer opment”, “Cross-Functional Cooperation”, “Top Manager knowledge is complementary to knowledge acquisition. Support”, “Training”) activate other factors and provide Customer knowledge focuses on generating new skills, appropriate conditions for CKM. For example, Cross-Func- products, and ideas to meet customer needs. tional Cooperation is necessary for collaboration and According to the results, Human factors such as “Individ- sharing customer knowledge through an organization. ual Competences and Skills” and “Trust between cus- Therefore, an organization should reorganize its organiza- tomer and company” are significant for enhancing CKM. tion structure based on customer value chains to establish A. KHOSRAVI et al. – Customer Knowledge Management in Enterprise Software Development… 295 [5] A. Nekrasov, et al. “Towards the Sea Ice and Wind Meas- a truly customer centred organization structure. Techno- urement by a C-Band Scatterometer at Dual VV/HH Polar- logical factors (“Collaboration System”, “CRM Technology ization: A Prospective Appraisal.” Remote Sens., vol. 12, Infrastructure”, and “Knowledge Map”) facilitate CKM in 3382, 2020. an organization. These factors provide the core IT infra- [6] P. Chaithanapat and S. Rakthin. 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Knowledge Management View," in: Collaborative, Trusted and Privacy-Aware e/m-Services. Springer, pp. 264-277, Irina Dyadyura Arash Khosravi ORCID ID: 0000-0002-5529-6406 ORCID ID: 0000-0003-0712-4447 Sumy State University Mahallat Institute of Higher Education Medical Institute Faculty of Engineering 40007 Sumy, Ukraine Mahallat, Iran e-mail: dyadyura@pmtkm.sumdu.edu.ua e-mail: arash.khosravi@pgu.ac.ir Morteza Rajabzadeh ORCID ID: 0000-0003-2776-5049 Mahallat Institute of Higher Education Faculty of Engineering Mahallat, Iran e-mail: rajabzadeh.m@gmail.com Viliam Zaloga ORCID ID: 0000-0001-7444-485X Sumy State University Faculty of Technical Systems and Energy Efficient Technologies Rymskogo-Korsakova st. 2, 40007 Sumy, Ukraine e-mail: zalogav@gmail.com http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Management Systems in Production Engineering de Gruyter

Customer Knowledge Management in Enterprise Software Development Companies: Organizational, Human and Technological Perspective

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de Gruyter
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© 2022 Arash Khosravi et al., published by Sciendo
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10.2478/mspe-2022-0037
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Abstract

In this study, Knowledge-Based View (KBV) and Theory of Technology in a Generic Customer Knowledge Manage- ment (CKM) Framework were assimilated to demonstrate the Organizational, Human and Technological anteced- ent factors that enable CKM processes to improve software product quality. A Theoretical CKM Framework was developed by extracting Human, Organizational and Technological factors from the literature, then, the “Tech- nique for Order of Preference by Similarity to Ideal Solution” (TOPSIS) Multi-Criteria Decision Making (MCDM) method was applied to find the importance level of factors to CKM development in software companies. The weight and priority of factors were determined by 31 experts in enterprise software development companies. The results show that, from an expert viewpoint, CKM antecedent factors are categorized into high priority and low priority groups. Organizational factors such as “Customer Involvement”, “Customer-Centric Culture” and “CKM Strategy Development” are high priority. Key words: qualimetry, knowledge management, enterprise software development, TOPSIS, summarizing indi- cator, multicriteria quality assessment, dimensionless scale INTRODUCTION and the overall success of the entire project [12, 15, 17, Product quality in organizations requires a long enhance- 18, 19]. Successful CKM in software companies improves ment process and mature business processes for product product quality. production [1, 2]. According to KBV, CKM are effective or- LITERATURE REVIEW ganizational factors that enhance software quality in soft- The rate of application of CKM in ES is low. For example, ware companies [3, 4]. Integrating Customer Knowledge according to an investigation of 22 software development (CK) in enterprise software development is still immature, companies that proposed their product in ELECOMP 2014 as it lacks a theoretical framework to fully capture CKM [5, (Big annual ICT exhibition in Tehran), 69% had no solution 6]. There are significant challenges regarding the transfer or guidelines for gathering customer knowledge. 81% of and integration of customer knowledge inside software them mentioned that the software production process in companies [7, 8, 9, 10]. A lack of senior management com- their companies is product centric rather than customer mitment to CKM, poor communication, a lack of cultural centric. There is a lack of systematic CKM processes in readiness, and a lack of customer management skills are many companies [5, 13, 20]. Ignoring the utilization of CK barriers to the design and implementation of CKM [9, 10, in several firms [21, 22, 23], an inadequate theoretical 11, 12]. Most major problems for the effective application framework for CKM antecedent factors and a lack of com- of CKM in many companies are organizational and not prehensive theoretical framework for CKM effects on technical [1, 2, 13, 14, 15, 16]. There is no doubt that ap- software quality in enterprise software development re- propriate communication and customer collaboration in flect a fundamental need for further exploration [1, 3, 9, different phases of Enterprise Software (ES) development 24, 25]. Most software companies in this study are Small project would help increase overall customer satisfaction © 2022 Author(s). This is an open access article licensed under the Creative Commons BY 4.0 (https://creativecommons.org/licenses/by/4.0/) 292 Management Systems in Production Engineering 2022, Volume 30, Issue 4 and Medium Enterprises (SMEs) [20, 24, 25, 26, 27, 28, 29, Taking these views into consideration, this study decided 30]. SMEs face resource constraints [1, 4, 6, 31]. Regard- to use 50 specialists for the data gathering stage. After dis- ing the high rate of failure in CKM projects [32, 33, 34, 35], tributing the survey questionnaire to 50 ES experts from determining important CKM success factors that decrease 13 different companies, 31 completed questionnaires the risk of failure is vital for managers and practitioners in were returned. software companies. The outcomes of this study help companies focus on high priority CKM factors and reduce TOPSIS Analysis organizational resource waste. Due to a history of poor In this study, we rank CKM success factors based on im- solutions coupled with technology failures, many compa- portance and relevance in ES development using TOPSIS. nies have a hard time justifying CKM initiatives [18, 23, 33, According to Cherniak, et al. [50], the TOPSIS procedure 36, 37, 38, 39, 40]. Understanding the antecedent weights has five steps. After forming an initial decision matrix, the helps software companies improve the success rate for procedure starts by normalizing the decision matrix. This CKM projects and motivate managers to implement CKM. is followed by building a weighted normalized decision Despite many studies that have examined CKM anteced- matrix in Step 2, determining the positive and negative ent factors in multiple contexts, none of them are com- ideal solutions in Step 3, and calculating separation prehensive enough to capture all factors into one single measures for each alternative in Step 4. The procedure framework. In this study, an empirical study was con- ends by computing the relative closeness coefficient. The ducted to investigate possible factors influencing CKM in set of alternatives (or candidates) is ranked according to ES development companies [41, 42]. The questions that the descending order of the closeness coefficient [51]. were asked in this study are: (a) What are the antecedent The procedure for the TOPSIS method consists of the fol- factors that affect CKM in an organization based on Hu- lowing steps: man, Organization and Technology frameworks? (b) What Given a set of alternatives, A = {A |i = 1, …, n} and a set of framework is appropriate to weigh and prioritize anteced- criteria, C = {C |i = 1, …, m}, ent factors using TOPSIS for ES development companies? where: 𝑋 = $𝑥& | 𝑖 = 1, ⋯ , 𝑛; 𝑗 = 1, ⋯ 𝑚1 denotes the set of !" GOAL OF THE WORK ratings and 𝑊 = $𝑤 5 | 𝑗 = 1, ⋯ , 𝑚1 is the set of weights. This paper evaluates the importance level of CKM critical Σ w = 1 = w + w + w + w + w = 0.066667 + 0.133333 + i 1 2 3 4 5 factors. This study proposes a framework to weigh and 0.2 + 0.266667 + 0.333333 = 1 prioritize CKM antecedent factors based on expert view- The first step of TOPSIS is to calculate normalized ratings points using TOPSIS in enterprise software development. by Eq. (1). Then we calculate the weighted normalized rat- ings by Eq. (2). OBJECTS AND METHODS OF RESEARCH #$ !" 𝑟̃ (𝑥) = , 𝑖 = 1, ⋯ , 𝑛; 𝑗 = 1, ⋯ , 𝑚 !" CKM Framework for the Software Companies (1) $ # %∑ #$ !%& !" This study investigates what of the extracted CKM ante- 𝑣0 (𝑥) = 𝑤 2 𝑟̃ (𝑥), 𝑖 = 1, ⋯ , 𝑛; 𝑗 = 1, ⋯ , 𝑚. (2) cedent factors [43] are suited for enterprise software de- !" " !" In the next step, the Positive Ideal Point (PIS) and the Neg- velopment companies. Appropriate techniques were cho- ative Ideal Point (NIS) are calculated (see Table 1) using sen to select suitable CKM antecedent factors for the Eq. (3). scope and purpose of this study. The TOPSIS method was ' ' ' ' ' used to choose appropriate factors and develop a frame- 8 𝑃𝐼𝑆 = 𝐴 = {𝑣0 (𝑥), 𝑣0 (𝑥), ⋯ , 𝑣0 (𝑥), ⋯ , 𝑣0 (𝑥)} ( ) * work for CKM for software development companies. = {(𝑚𝑎𝑥 𝑣0 (𝑥)|𝑗 ∈ 𝐽 ), (𝑚𝑖𝑛 𝑣0 (𝑥)|𝑗 ∈ 𝐽 )|𝑖 = !" ( !" ) ! ! 1, ⋯ , 𝑛} (3) Data Collection + + + + 𝑁𝐼𝑆 = 𝐴 = {𝑣0 (𝑥), 𝑣0 (𝑥), ⋯ , 𝑣0 (𝑥), ⋯ , 𝑣0 (𝑥)} ( ) " * After extracting the CKM impact factors, the priority and = {(𝑚𝑖𝑛 𝑣0 (𝑥)|𝑗 ∈ 𝐽 ), (𝑚𝑎𝑥 𝑣0 (𝑥)|𝑗 ∈ 𝐽 )|𝑖 = !" ( !" ) weight of the factors were used to select appropriate fac- ! ! 1, ⋯ , 𝑛} tors for ES development. This study consulted with ES de- where: velopment experts using a survey questionnaire designed J and J are the benefit and the cost attributes, respec- 1 2 to find out what extracted impact factors are most im- tively. portant for ES. The survey questionnaire included a list of CKM enablers and their definitions. This study asked ex- Table 1 perts to evaluate each factor using a 5-point Likert scale Positive Ideal Point (PIS) and the Negative Ideal Point (NIS) (not important, low important, important, moderate im- Max Vi1 Max Vi2 Max Vi3 Max Vi4 Max Vi5 portant, and very important). When it comes to MCDM 0.03306122 0.059446777 0.065833774 0.094859067 0.133627638 procedures, no guidelines exist for deciding the number Min Vi1 Min Vi2 Min Vi3 Min Vi4 Min Vi5 of respondents. As TOPSIS is not based on statistics, a 0 0 0.005486 0.007905 0 modest sample size was adequate [44, 45, 46]. In the opin- The following step is to calculate separation from PIS and ion of Dyadyura [47], MCDM such as TOPSIS and AHP (An- NIS by the alternatives. The separation values are meas- alytic Hierarchical Process) are scientifically applicable ured using a Euclidean distance given as: and do not require a large sample size. In the study con- ducted by Trishch, et al. [48, 49], MCDM procedures were ' * ' 𝑆 = ∑ [𝑣0 (𝑥) − 𝑣0 (𝑥)] , 𝑖 = 1, ⋯ , 𝑛 A (4) ! !" ",( " used to rank factors based on the viewpoint of 12 experts. A. KHOSRAVI et al. – Customer Knowledge Management in Enterprise Software Development… 293 The final ranking shows the overall viewpoint of 31 ex- + * + 𝑆 = ∑ [𝑣0 (𝑥) − 𝑣0 (𝑥)] , 𝑖 = 1, ⋯ , 𝑛 A (5) ! !" ",( " perts on the significance of each factor for enhancing CKM ' + in the enterprise software development domain. The 𝑚𝑎𝑥{ 𝑣0 (𝑥)} − 𝑣0 (𝑥) = 𝑚𝑖𝑛{ 𝑣0 (𝑥)} − 𝑣0 (𝑥) = 0. (6) !" " !" " overall viewpoint of the experts indicated that “Customer Accordingly, the similarities to PIS are calculated using Eq. Involvement” and “Customer-Centric Culture” have the (7). most significant effect on enhancing CKM in software .(0 ) ∗ ! 𝐶 = , 𝑖 = 1, ⋯ , 𝑛 (7) ! ( ' companies to achieve quality software. However, “Privacy [.(0 )'.(0 )] ! ! for customers” and “Intellectual Property” have a less sig- where: nificant effect on enhancing CKM in software companies. 𝐶 ∈ [0,1] ∀𝑖 = 1, ⋯ , 𝑛 (8) * It is clear from Table 2 that the distance between the rank Finally, the preferred orders are ranked according to C in of “Key Customer Management” and “Knowledge Map” is descending order. In Table 2 the ranks of 22 CKM factors considerable. The factor rankings before “Key Customer are presented. Management” are very near to each other (0.3 < Ranks > Table 2 0.4). Distance from positive and negative ideal Furthermore, the ranks of the factors after “Knowledge ' + ' + ∗ Factors 𝑫(𝑺 ) 𝑫(𝑺 ) 𝑫(𝑺 ) + 𝑫(𝑺 ) 𝑪 𝒊 𝒊 𝒊 𝒊 𝒊 Map” are very near each other as well (0.4 < Ranks > 0.6). Customer Thus, there is a breakpoint between the rank of these two 0.08272 0.120818 0.203538 0.59359 involvement factors (“Key Customer Management” and “Knowledge Customer-cen- 0.091899 0.132759 0.224658 0.590937 Map”) that can categorize the antecedent factors into two tric culture groups. The first group refers to high priority CKM ante- CKM Strategy 0.096197 0.138431 0.234628 0.590003 cedent factors (Rank > 0.5) and the second group refers to development low priority CKM antecedent factors (Rank < 0.4). 11 out Collaboration 0.086869 0.123678 0.210548 0.587413 of 22 factors are in the high priority CKM antecedent system Cross-func- group. This high priority group includes Organizational tional 0.086056 0.118937 0.204993 0.580199 factors (“Customer Involvement”, “Customer-Centric Cul- cooperation ture”, “CKM Strategy Development”, “Cross-Functional Individual Cooperation”, “Senior Management Support”, “Train- competences 0.092332 0.123465 0.215798 0.572135 ing”), Human factors (“Competencies and Skills”, “Trust and skills between customer and company”) and Technological fac- Trust tors (“CRM Technology Infrastructure”, “Collaboration between 0.084384 0.110967 0.19535 0.568038 System”, “Customer Knowledge Map”). The managers of customer software companies must give great attention to the suc- and company cessful implementation and deployment of CKM. This Top manager 0.088304 0.114491 0.202795 0.564566 study proposed a CKM framework for software compa- support CRM nies based on the highest priority CKM antecedent fac- technology 0.093538 0.118261 0.2118 0.558364 tors. infrastructure Training 0.087253 0.105486 0.192739 0.547299 DISCUSSION Knowledge After developing a theoretical framework based on 22 an- 0.094539 0.112504 0.207043 0.543385 map tecedent CKM factors extracted from the literature [52]. Key customer 0.123427 0.079196 0.202623 0.390853 The framework was evaluated by 31 experts in enterprise management software development in Iran. The TOPSIS method was Reward 0.123696 0.076964 0.20066 0.383553 used to rank the factors and it shows their significance for system enhancing CKM to improve software quality in software CK Oriented BP 0.128879 0.080094 0.208973 0.383275 development companies. Based on the result of the TOP- CK Quality 0.13581 0.081571 0.21738 0.375244 SIS analysis, some findings from previous studies were Individual 0.123018 0.071631 0.194649 0.368001 Motivation supported. Program cham- As discussed in the previous section, based on factor rank- 0.144845 0.075245 0.22009 0.341885 pion ings, the antecedent factors are classified into factors of Integrated high importance factors and factors of low importance. In knowledge Re- 0.130877 0.06798 0.198857 0.341851 the high importance group, the first three are Organiza- pository tional factors, which mean that Organizational CKM fac- Community 0.153343 0.077045 0.230388 0.334415 tors have more priority than Human and Technological of practice factors. CKM is based on people and social interaction, Social Media 0.147994 0.071706 0.2197 0.32638 where the organization is responsible for establishing the Provide right conditions for CKM, and information and communi- Privacy for cus- 0.137138 0.061561 0.198699 0.309822 cation technology helps to facilitate this [53]. This finding tomers Respect for was supported by the Theory of Technology. The results Intellectual 0.145573 0.065002 0.210576 0.308688 Property 294 Management Systems in Production Engineering 2022, Volume 30, Issue 4 of research work [54] noted that human actions are ena- This finding is in line with recent studies by [62] and [63], bled and constrained by organizations. However, the rules who identified that appropriate training is required to and the structures of organizations are the result of previ- make sure employees have enough IT skills and expertise ous actions. Technology is an instantiation of some of the to effectively absorb, share and utilize CK. The results of rules and resources constituting the structure of an organ- research work [64] noted that for successful CKM, three ization. Technology is created and changed by human ac- types of customer knowledge competencies are required: tion, yet it is also used by humans to accomplish actions. customer knowledge acquisition skills, customer Thus, it is clear from the results that for successful CKM knowledge sharing skills and customer knowledge use development, managers of software companies must fo- skills. The results of research work [65] highlighted the im- cus on organizational factors to enable the development portance of trust between customer and company for im- of other factors. proving the process of customer knowledge absorption. “Customer Involvement”, “Customer-Centric Culture” The results of research work [66] mentioned that one of and “CKM Strategy Development” were given a high pri- the key challenges in absorbing knowledge from custom- ority, and this confirms the result of works developed by ers in software development projects is a lack of trust be- [55, 56, 57]. Moreover, “Customer Privacy” and “Cus- tween customers and development teams. Organizational tomer’s Intellectual Property” have a lower priority and antecedent factors such as CKM strategy, top manage- experts consider these factors not very important for CKM ment support, and training are important for enhancing development. The results of research work [58] noted employees skills and providing a trusting environment that customers’ wishes, needs, and preferences influence [67]. the concept and design of a product or service. It was sug- The result of this study shows that from the 22 extracted gested that customers should be involved within the de- antecedent factors, 11 factors are in the highly important velopment phases of a product/service, which includes group based on 31 experts’ viewpoint in software devel- Idea Generation, Concept Development, Product Design, opment. Implementing and deploying CKM successfully in Prototyping/Testing, and Maintenance. At each different enterprise software development companies to improve stage, value is created collaboratively as organizations software quality strongly depends on these high priority gain insight into customer preferences and ideas based on factors. This finding is supported by the results of the re- continuous interaction and feedback from costumers [59, view [68], According to [69, 70], all of the antecedent fac- 60]. Important technological factors such as “collabora- tors in the high priority group have high iteration in the tion system”, “CRM Technology Infrastructure” and literature. In [71] shows that CKM was used in a variety of “Knowledge Map” facilitate absorbing, storing, organiz- contexts [72, 73, 74] provided evidence and supports our ing, and distributing customer knowledge. The knowledge findings, since all high priority factors were already used acquired is codified and stored in corporate databases in IT companies. This study’s findings are similar to past and knowledge warehouses. CRM Technology Infrastruc- findings, but this study is more comprehensive and con- ture helps companies to absorb and store all customer siders the entire CKM antecedent factors mentioned in transitions and provides a repository of feedback. previous studies. Some of the high frequency CKM ante- Knowledge Maps are used to organize explicit and tacit cedent factors in the literature were not selected in the knowledge and collaboration systems provides a collabo- high priority group because of the specific conditions of rative environment for sharing CK inside organizations software development in Iran. These factors may be more and between organizations and customers. significant in other countries or other contexts. “Customer-Centric Culture”, “Top Management Sup- ports” and “Training” are important organizational factors CONCLUSIONS that facilitate the absorption, sharing and utilization of The findings of this study build and expand CKM in enter- customer knowledge. The results of research work [61], prise software development companies. 22 factors were successful CKM requires the transformation of organiza- extracted from the CKM literature and categorized based tions from a product-centric focus to a customer centric on the Theory of Technology into Organizational, Human, focus. To provide a customer-centric culture that per- and Technological factors. According to the findings from ceives customers as a valuable source of knowledge, top the TOPSIS method, 11 factors from the extracted ante- management must inspire an organizational culture that cedent factors are in the highly important group based on motivates employees to acquire, share and use CK. Organ- the opinions of 31 software development expert. These izations need to change business processes and shape factors are critical for successfully implementing CKM. their organizational culture and routines to utilize the po- High priory organizational factors (“Customer Involve- tential of CRM systems to generate customer knowledge ment”, “Customer-Centric Culture”, “CKM Strategy Devel- and optimize benefits. Development of customer opment”, “Cross-Functional Cooperation”, “Top Manager knowledge is complementary to knowledge acquisition. Support”, “Training”) activate other factors and provide Customer knowledge focuses on generating new skills, appropriate conditions for CKM. For example, Cross-Func- products, and ideas to meet customer needs. tional Cooperation is necessary for collaboration and According to the results, Human factors such as “Individ- sharing customer knowledge through an organization. ual Competences and Skills” and “Trust between cus- Therefore, an organization should reorganize its organiza- tomer and company” are significant for enhancing CKM. tion structure based on customer value chains to establish A. KHOSRAVI et al. – Customer Knowledge Management in Enterprise Software Development… 295 [5] A. Nekrasov, et al. “Towards the Sea Ice and Wind Meas- a truly customer centred organization structure. Techno- urement by a C-Band Scatterometer at Dual VV/HH Polar- logical factors (“Collaboration System”, “CRM Technology ization: A Prospective Appraisal.” Remote Sens., vol. 12, Infrastructure”, and “Knowledge Map”) facilitate CKM in 3382, 2020. an organization. These factors provide the core IT infra- [6] P. Chaithanapat and S. Rakthin. 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Knowledge Management View," in: Collaborative, Trusted and Privacy-Aware e/m-Services. Springer, pp. 264-277, Irina Dyadyura Arash Khosravi ORCID ID: 0000-0002-5529-6406 ORCID ID: 0000-0003-0712-4447 Sumy State University Mahallat Institute of Higher Education Medical Institute Faculty of Engineering 40007 Sumy, Ukraine Mahallat, Iran e-mail: dyadyura@pmtkm.sumdu.edu.ua e-mail: arash.khosravi@pgu.ac.ir Morteza Rajabzadeh ORCID ID: 0000-0003-2776-5049 Mahallat Institute of Higher Education Faculty of Engineering Mahallat, Iran e-mail: rajabzadeh.m@gmail.com Viliam Zaloga ORCID ID: 0000-0001-7444-485X Sumy State University Faculty of Technical Systems and Energy Efficient Technologies Rymskogo-Korsakova st. 2, 40007 Sumy, Ukraine e-mail: zalogav@gmail.com

Journal

Management Systems in Production Engineering – de Gruyter

Published: Dec 1, 2022

Keywords: qualimetry; knowledge management; enterprise software development; TOPSIS; summarizing indicator; multicriteria quality assessment; dimensionless scale

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