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ISSN : 1598-7248 (Print)
ISSN : 2234-6473 (Online)
Industrial Engineering & Management Systems Vol.17 No.4 pp.719-729
DOI : https://doi.org/10.7232/iems.2018.17.4.719

Analysis of Technology Acceptance on the Effectiveness of the Electronic Supply Chain Management and Inventory Systems in Ukrainian Banking Industry

Iryna A. Markina, Olha A. Bilovska, Olena I. Yakovenko, Radyslava I. Shevchenko-Perepyolkina
Poltava State Agrarian Academy, Poltava, Ukraine
V. N. Karazin Kharkiv National University, Kharkiv, Ukraine
Izmail State University of Humanities, Izmail, Ukraine
* Corresponding Author, E-mail: iriska7@ukr.net
April 11, 2018 November 29, 2018 September 17, 2018

ABSTRACT


A lot of people’s access to the Internet all around the world and expansion of electronic communications between people and organizations through virtual world has provided grounds for trade interactions. Although a lot of research has been conducted inventory systems, yet in these research different theoretical frameworks have been utilized. But in electronic management, not many research have been conducted in inventory systems especially in private banking area; therefore, this subject has been considered as the main objective of this research. This research aims at investigating technological readiness in Technology Acceptance Model, and the use of E-CRM of Ukrainian bank in northern Kiev. Research method was descriptive applied library search. Data was collected through a standardized questionnaire whose reliability and validity were approved. The sample of this research was all branch managers, their assistants, and the officers working in northern Kiev branches. The number of the subjects, based on Kukran formula was 218 which was determined via random selection. SPSS 22 and Smartpls 3 were used as data analysis software. The result of this research showed that advantage adaptability, observations, experimentation, daily activities, organization, and environment play a pivotal role in accepting E-CRM. At the end of the research some suggestions on research hypotheses were provided.



초록


    1. INTRODUCTION

    A lot of successful organizations reiterate that maintaining a sustainable relationship with inventory can keep them firm and pioneer in competitions. This strategy is different in different organization based on the needs of the organization and the inventories (Verhoef, 2003). Inventory system provides a general and clear picture of what is needed from inventory in details. This establishes a specific relationship between inventories and organization and accordingly no sales chances and inventory system subsequently will be lost. Because of the increasing competition, organizations must have an exact knowledge of their environment and specifically of the inventories, who are the main factor in keeping organizations alive, to be able to survive in this arena. This way organizations can find the inventory’ needs in order to effectively interact with environments in time. Therefore, a large number of successful organizations in the world have managed to prioritize their external environment and precise understanding of the needs of the inventory through environmental data collection systems (Payne and Frow, 2005).

    Considering the cultural, social, technological, and other changes that have taken place, it is not possible to merely compete with cheaper, better, or stronger products and competitive advantage will not be realized only by depending on variety of products but through increasing relationship with inventories (Reinartz et al., 2004). inventories’ expectations has been on the rise during the recent years and a factor in turning the element of inventory to a necessity in today’s inventory-centered commercial environments. Researches emphasize that costs of attracting new inventories are higher than retaining the current ones. One of the major reasons in this regard is the marketing an advertisement costs. It means that, instead of having a variety of products organizations must distinguish between the inventories, and focus on the inventory’ share rather than on market share. Researches also show that organizations must not only try to retain their current inventories (Da’avi and Nazari, 2014).

    In recent years that term “inventory system” has drawn a lot of attention in marketing and information technology. Academics, software Sellers, advisers, and business people have been very active in this field, and developed the concept of this slogan, i.e., Organization’s efforts must provide and offer higher values to inventory. Organizations admit that inventories are their most important asset. Therefore inventory system, to them, is a lucrative interaction which requires proper management.

    In electronic management of inventory system, especially in private banking, so far there have not been comprehensive researchers; therefore, this point was taken as the main issue of this research. On the other hand, the present research aims at providing Technology Acceptance Management model to increase the efficiency of electronic management of inventory system in Kiev bank.

    2. THEORETICAL FOUNDATIONS OF THE RESEARCH

    2.1. Supply Chain Management

    That term “Supply chain management” is in fact a strategic system in collecting inventories’ commercial needs and behaviors which aims at establishing stronger relationships with them. Strong relationship with inventories, is in fact, the most important key to success for every business. CRM consists of three major parts: relationships, inventories, and management. Supply chain management and inventory systems includes instructions, methods, processes, and strategies of the organization to merge their inventories’ needs and keep their information.

    Inventory system is referred to as the end user, who in value creating relationships, play a supportive role. Relationship means creating more loyal and profit making inventories through a learning relationship, and management means creativity and ability tools to steer an inventory- centered business and put the inventory in the center of organization’s processes and experiences. Today, supply chain management and inventory systems is of strategic importance. In difficult competition circumstances, timely and organized relationship with inventories is the best way to increase inventory, sales, at the same time cut the cost. Taking the scores into account makes supply chain management and inventory systems and organization a kind of commercial strategy.

    Some of the supply chain management performances are as follows: data warehousing, data mining, and it is also a tool for decision-making and providing reports.

    2.2. Electronic Supply Chain Management and Inventory Systems

    Supply chain management is a pivotal and important issue in marketing, but is yet not entirely accepted. Triznova et al. (2015) have considered this approach as a process, a strategy, a philosophy, and a technological tool or capability. They have stated that inventory system is a commercial strategy to acquire long-term competitive advantage through optimizing time and quality of delivery to inventories, and at the same time, extracting commercial values. In straightforward terms, the aim of electronic supply chain management and inventory systems is understanding values and treating inventories in a better way to increase their loyalty and profit of the company accordingly. In other words companies must rely on reconstructing their relationship with inventories more than depending on the conventional model of “try to sell more.” There is a large number of researches indicating that technological advances that have taken place during the recent years have had considerable effect on organizations’ trade processes and output. Among the mentioned technological advances, maybe the emergence of the Internet has been the most important one which has affected the world of supply chain management. This achievement, with its interactive nature, has provided very good grounds for managers to establish continuous and quality relationship with the inventories. In addition to unique chances in establishing relationship with shareholders, attraction technology as an effective force in attracting inventories, an access to technical infrastructure in order to do data mining and warehousing, high speed and efficiency of inventory system are among other key Internet features in supply chain management. It is crystal clear that the Internet provides an extraordinary power in creating better inventory system. All these points indicate that now there is a new and developed type of supply chain management referred to as electronic supply chain management and inventory systems. Although Internet provides promising grounds in implementing supply chain management, yet to achieve success in electronic supply chain management and inventory systems the only way is consistent and appropriate planning. Therefore, evaluating the performance of activities of electronic supply chain management and inventory systems in Internet interactions and determining the effectiveness of this communication channel in supply chain management plans are of great importance. Either of the two CRM concepts and Electronic Technologies have different implications in organizations, but merging these two, i.e., electronic supply chain management and inventory systems causes synergy in creating new values for organizations (Trainor et al., 2014).

    2.3. Information Technology Acceptance

    Accepting is a multi-dimensional phenomenon and a combination of key variables such as conceptions, ideas, approaches, individual characteristics, and the extent of their involvement in information technology. Users’ acceptance is defined as “an obvious interest in the group in using information and communication technology in order to perform the tasks these technologies have been designed to support”.

    Remarkable expansion of technology in business processes to offer higher quality to inventories has led to the emergence of more complicated technologies in trading. These new technologies are being used to satisfy inventories, but researchers have shown of that inventories do not easily and equally accept new technologies (Magotra et al., 2016). Table 1 introduces the most important models in accepting information technologies.

    2.4. Technology Acceptance in the Bank

    As the access to and use of information and communication technology, and more specifically the Internet, has been eased, no channels have been created for advertising, purchasing, and selling products. So, in recent years new business models have been released. E-commerce and electronic business are among the most important parts of these models. In Electronic Commerce, business processes are electronically supported and linked. In electronic business, in addition to sales and purchase processes, supply and production also depend on electronic environment (Zuccato, 2007). In recent years researchers have paid more attention to the importance of technology of rendering and accepting electronic services in banking industry (Dauda and Lee, 2015). Banking industry has changed from conventional telephone banking to electronic banking and subsequently to Internet banking. Acceptance of the Internet and electronic banking has had great effects on absorbing inventories and has led to a rise in banking activities, offering more services, attracting more investments, and balancing debts (Dauda and Lee, 2015; Sahay and Mohan, 2003). Banking industry has been affected by information and communication technology revolution and has therefore developed and multiplied its channels to render services. These ongoing changes has given importance to the use of modern channels of rendering services. Therefore, banks must manage these changes and try to have positive effect on their inventories’ behavior and attitude. Moreover, it is a fact that banks have greatly invested on modern technologies, and if inventories do not use these technology banks will be in great loss. In general, different factors affect the acceptance of electronic banking by the inventories, some of which are demographic features, motivation, and inventories abilities and attitudes. Banks have greatly use technologies in offering services as methods could support services are which where conventionally offered by staff members of banks. But these technologies can only improve performance when accepted by both inventories and staff members (Zhu and Chang, 2014).

    3. REVIEW OF RELATED LITERATURE

    In this section, related domestic and international studies have been presented.

    We have conducted the research and steadied that effect of knowledge management and supply chain management in Kiev Supervision headquarters. Research findings indicate that knowledge management through sources of knowledge have positive and significant effect on different aspects of supply chain management, i.e., inventory system. Triznova et al. (2015), in a research, investigated the inventory system related management system in banking system. The results show that the supply chain management system can help retain present inventories and absorb new ones. Banks use some methods including supply chain management, inventory system analysis, organizational strategy, and services mechanisms which improve inventory system efficiency. Supply chain management is a strategy to absorb new inventories and to retain them. Supply chain management involves operations including all direct inventory related activities. In other research, conduct of the research titled: “A study of the effect of implementing electronic supply chain management and inventory systems on inventory system quality in Kiev bank.” The subjects of this research where inventories of Kiev bank who have come to this conclusion that electronic supply chain management and inventory systems has positive effect on the quality of services, the quality of inventory system, and on the performance of the bank. Moreover, quality of inventory-oriented services has positive effects on the quality of inventory system, and eventually the quality of inventory system has positive effects of the performance of the bank. In another research, investigated the supply chain management system in banking system. The results showed that through supply chain management, banks can shorten the sales cycle and increase the inventory in establishing closer relationship and accordingly increase the income. Josiassen et al. (2014) conducted the research titled: “Do all dimensions of CRM affect the performance of companies?” Results showed that all the three dimensions of CRM capabilities have positive effect on performance of hotels, while previous a researches, on the contrary, showed that making investments on CRM did not have positive effect on performance of hotels, but there is a significance relationship between accountability and performance in larger company. Another research conducted by Santoso and Erdaka (2015) investigated inventory in Common Consumption Model in supply chain management for services offered on Electronic Commerce related system in Indonesia. Findings show that initial understanding of benefiting from advantages, initial delays, and initial monetary value have remarkable effect on inventory which can be measured by the number of profound transaction and inventories’ lifetime. Foroughi et al. (2012), in their research, investigated the effect of costs, acceptance of technology, and inventory system on supply chain management systems efficiency. Results showed that acceptance of technology in organizations with infrastructural capabilities, ease of use, and electronic timing systems positively affect the efficiency of electronic supply chain management and inventory systems (Dehning et al., 2007).

    4. CONCEPTUAL RESEARCH MODEL

    In order to investigate the acceptance of technology in organizations various models have been proposed. The muddled chosen in this research was proposed by Wu and Wu (2005). This model is said to be complementing technology acceptance models proposed prior to the research conducted by Wu and Wu (2005).

    Based on the research model, the following hypotheses are investigated:

    • The attitude has a significant effect on behavioral intention in using E-CRM

    • Trialability have a significant effect on the attitude in using E-CRM

    • Relative advantage has a significant effect on the attitude in using E-CRM

    • Complexity has a significant effect on the attitude in using E-CRM

    • Compatibility has a significant effect on the attitude in using E-CRM

    • Observability has a significant effect on the attitude in using E-CRM

    • Daily activities have a significant effect on the attitude in using E-CRM

    • Personal qualities have a significant effect on the attitude in using E-CRM

    • Organizing has a significant effect on the attitude in using E-CRM

    • Environment has a significant effect on the attitude in using E-CRM

    • Complicatedness has a significant effect on the proportional advantage in using E-CRM

    • Proportional advantage has a significant effect on behavioral intention in using E-CRM

    4.1. Research Method

    The research methods is descriptive applied library search. The data was collected through a standardized questionnaire whose validity and reliability were approved. The subjects of this research where all the branch manager and their assistants and the officers working at northern Kiev branches. There were 218 subjects chosen based on Kukran formula through random selection. A standardized questionnaire was used as a data collecting instrument taken from the research conducted. This questionnaire is used to measure relative advantage, complexity, compatibility, observability, trialability, daily activities, personal, organizing, environment, attitude, and behavioral intention. SPSS 22 and Smartpls 3 software were used for data analysis purposes. Table 2

    4.2. Research Findings

    4.2.1. Investigating Theoretical Models Test in PLS

    4.3. Composite Reliability of the Constructs

    In order to investigate the composite reliability of each of the constructs Dillon-Goldstein coefficient (pc) was used. As PLS, unlike multiple regression, uses the subjects’ scores to do the analyses, it is essential to consider their load and weight of each of these in calculating reliability. Meanwhile Cronbach Alpha coefficient gives equal weight to each and shows a lower reliability. Accordingly pc coefficient was used. Acceptable pc values must be the equal to or above 0.7 (Fornell and Larcker, 1981).

    4.4. Checking the Construct Validity

    Fornell and Larcker (1981) propose two measures to check the validity

    • Convergent Validity (including Confirmatory Validity Test and test of Average Variance Extracted (AVE))

    • Discriminant Validity (including Fornell and Larcker test)

    Figure 1

    4.5. Convergent Validity

    If the t value of the indicators of the studied constructs is smaller than 1.96, they are not significant enough to be used for measurement purposes. Therefore, they must be ignored in the process of analysis; on the other hand if the t value of the indicator is above 1.96, they will be taken into account in the process of analysis. In this case this indicator is precise enough to be used for measuring the construct or the quality. The following table shows the t value for indicators of each construct.

    As the t values for question CL2 are smaller than 1.96, this question will be omitted from the research. The same process will be repeated for the remaining questions.

    As it can be seen the t values for all questions is more than 1.96. Therefore, the construct validity shows that the remaining indicators provide appropriate constructs for measuring the studied aspects in the research model. Table 3-4, 5

    4.6. Average Variance Extracted

    Accordingly the third indicator to check the validity, is the average variance extracted (Fornell and Larcker, 1981). Fornell and Larcker (1981) recommend values more than 0.5 for AVE. This means that the certain construct meets its indicators variance as much as 50% or more. Table 6

    4.7. Discriminant Validity

    • Fornell-Larcker Criterion (studying the correlation between latent variables)

    In PLS Software, Discriminant validity is measured in two ways: 1) Cross-loading method and 2) Fornell- Larcker Criterion where the relationship between a construct and its indices is in comparison with their relationship between that construct and other constructs. The present research has used Fornell-Larcker Criterion to measure the discriminant validity shown in the table below. Like the other two criterion, validity measures the diagnosis validity at latent variables level. According to this criterion, a latent variable, as compared to other latent variables, must have a higher dispersion among its constructs. The second criterion is that the square root of AVE of a construct must be greater than the correlation of that construct with other constructs. This shows that the correlation of that construct with its indicators is greater than its correlation with other constructs.

    As in each line, the entry on the main diameter is greater than other entries on the same line (i.e., the correlation of that construct with its own indicators is greater than its correlation with other constructs), the validity of the latent constructs is approved.

    4.8. Testing Research Hypotheses

    In this section, firstly the hypotheses mentioned in chapter one were tested, and then the main research question was analyzed. As every question on the questionnaire has a score, the average of the scores was used in order to answer the hypotheses. In order to test the conceptual model and the research hypotheses, structural equations model based on the partial least square method was utilized. Smart PLS software was used accordingly.

    The Figure 2, a conceptual model in Smart PLS software, shows the relationship between the factors defined in the research. The conceptual model shows the relationships between the variables whose accuracy or inaccuracy has not been tested against empirical data.

    4.9. Conceptual Model Test in PLS

    4.9.1. R² Criterion

    Reliability and validity of the external model estimates allow evaluation of internal path model estimates. The essential criterion for assessing coefficient of determination structural model (R² is the exogenous latent (dependent latent) variables). Zaidullina and Demyanova (2017) describes values 0.67, 0.33, 0.19 for the exogenous latent as remarkable, average, and weak respectively. If the constructs of a certain internal model explain exogenous latent variables only with 1 or 2 endogenous latent (independent latent), an average R² of 0.33 is acceptable. But if the exogenous latent variables depend on several endogenous latent variables, then the value of (R²) must be at least at the acceptable level of 0.67. Coefficient of determination values for dependent latent variables of the research are shown in Tables 7 and 8.

    4.10. Significance of coefficients

    Figure 3, shows the observed and the latent variables as well as the path coefficients and loads. The numbers that can be seen between the latent variables of the model (variables shown in oval shape) and observed variables (variables in rectangular shapes which are the latent variables subcomponent) indicate the loads. The equations defined among the latent variables are the very research hypotheses, and the numbers shown on these equations are the path coefficients. Table 9

    4.11. Testing Research Hypotheses

    As the table shows, the coefficient of attitude on behavioral intention in using E-CRM is also equal to 0.281964 and the t observed value is 2.568011. Since the t value in the resulting construct (2.568011) is greater than the t value at 95% level (1.96), therefore, the hypothesis which says there is a significant relationship between attitude and behavioral intention using E-CRM at 95% level. Moreover, the extent of coefficient between the two variables is positive. This means that as the attitude improves, the behavioral intention using E-CRM also improves. The results for other hypotheses are also shown in the table.

    5. Conclusion and Suggestions

    • As there is a significant effect for the attitude on behavioral intention using E-CRM, it is suggested that bank managers provide their staff members with instructions and manuals to familiarize them with the benefits and the use of supply chain management systems. It is also suggested that the Kiev banks inform their staff members of positive results emanating from implementing these systems in domestic and international banks so that these results can affect their attitudes towards E-CRM positively.

    • As there is a significant effect for the trialability on the attitude towards E-CRM, it is suggested that Kiev bank managers classify their staff members based on their abilities in learning, and provide them with opportunities to learn E-CRM. This causes the staff members to have better attitude while using these systems.

    • As there is a significant effect for the relative advantage on the attitude towards using E-CRM, it is almost unanimously agreed that there is an advantage for the electronic inventory system systems, yet it is necessary to provide partial awareness to the staff members on the improvements made by these systems.

    • As there is a significant effect for compatibility on the attitude towards using E-CRM, one of the most important worries of the people in facing new technologies is how they can make their activities compatible with the new methods provided in these technologies. Therefore, it is suggested that, before they take any actions in implementing these technologies, banks train their staff members in doing so.

    • As there is a significant effect for observability on the attitude towards using E-CRM, it is suggested that bank managers hold regular meetings in order to provide reports on the results of implementing these systems. This will lead to the actual implementation of these systems.

    • As there is a significant effect for daily activities on the attitude towards using E-CRM, it is suggested that the staff members of the bank share their experiences in using electronic inventory system systems so that they can manage their daily activities well.

    • As there is a significance effect for personal qualities on the attitude towards using E-CRM, it is clear that the personal qualities of different individuals are different from each other and there is no single prescription for everyone. Therefore, it is suggested that managers apply much care in assigning responsibilities, which have been created because of the emergence of new inventory system in organizations, and take the knowledge and information of the staff members into account.

    As there is a significant effect for organizing on the attitude towards using E-CRM, it is clear that the use of modern technologies in inventory system is not necessarily useful in all organizations. Perhaps the emergence of these technologies can cause a change in the general construct of the organization and negatively affect the performance of the staff members. Therefore, it is suggested that, in order to prevent these general changes to occur, this system be implemented tentatively and in case of positive feedback it can be used in other parts of the organization.

    Figure

    IEMS-17-719_F1.gif

    Conceptual model.

    IEMS-17-719_F2.gif

    Conceptual model in the software.

    IEMS-17-719_F3.gif

    Tested research model (t values, path coefficients, and factor loadings.

    Table

    Introducing the Most Important Models in Accepting Information Technology

    Symbols

    To Composite reliability values

    t Values for validity approval purposes in the measurement model

    t Values for validity approval purposes in the second modified model in the measurement model

    Checking AVE values

    The values of square root of AVE and the correlations

    Determination coefficient values

    Testing Research Hypotheses

    REFERENCES

    1. Da’avi, S. and Nazari, M. (2014), A conceptual framework in implementing Social-CRM in Pedarekhoob chain restaurants, International Conference on Economics, Accounting, Management and Social Sciences, Poland, Varsovie, 361-366.
    2. Dauda, S. Y. and Lee, J. (2015), Technology adoption: A conjoint analysis of consumers’ preference on future online banking services, Information Systems, 53, 1-15.
    3. Dehning, B. , Richardson, V. J. , and Zmud, R. W. (2007), The financial performance effects of IT-based supply chain management systems in manufacturing firms, Journal of Operations Management, 25(4), 806-824.
    4. Foroughi, A. , Rasoulian, M. , and Esfahani, M. J. (2012), Prioritize strategies of university by using SWOT analysis and ANP method, American Journal of Scientific Research, 46, 83-91.
    5. Fornell, C. and Larcker, D. F. (1981), Evaluating structural equations models with unobservable variables and measurement error, Journal of Marketing Research, 18(1), 39-50.
    6. Josiassen, A. , Assaf, A. G. , and Cvelbar, K. L. (2014), CRM and the bottom line: Do all CRM dimensions affectfirm performance?, International Journal Hospitality Management, 36, 130-136.
    7. Magotra, I. , Sharma, J. , and Sharma, S. K. (2016), Assessing personal disposition of individuals towards technology adoption, Future Business Journal, 2(1), 81-101.
    8. Payne, A. and Frow, P. (2005), A strategic framework for supply chain management, Journal of Marketing, 69(4), 167-176.
    9. Reinartz, W. , Krafft, M. , and Hoyer, W. D. (2004), The customer relationship management process: Its measurement and impact on performance, Journal of Marketing Research, 41(3), 293-305.
    10. Sahay, B. and Mohan, R. (2003), Supply chain management practices in Indian industry, International Journal of Physical Distribution & Logistics Management, 33(7), 582-606.
    11. Santoso, A. S. and Erdaka, A. (2015), Customer loyalty in collaborative consumption model: Empirical study of CRM for product-service system-based e-commerce in Indonesia, Procedia Computer Science, 72, 543-551.
    12. Trainor, K. J. , Andzulis, J. M. , Rapp, A. , and Agnihotri, R. (2014), Social media technology usage and customer relationship performance: A capabilities-based examination of social CRM, Journal of Business Research,67(6), 1201-1208.
    13. Triznova, M. , Maťova, H. , Dvoracek, J. , and Sadek, S. (2015), Customer relationship management based on employees and corporate culture, Procedia Economics and Finance, 26, 953-959.
    14. Verhoef, P. C. (2003), Understanding the effect of customer relationship management efforts on customer retention and customer share development, Journal of Marketing, 67(4), 30-45.
    15. Wu, I. L. and Wu, K. W. (2005), A hybrid technology acceptance approach for exploring e-CRM adoption in organizations, Behaviour & Information Technology, 24(4), 303-316.
    16. Zaidullina, C. and Demyanova, O. (2017), Enhancement of the choice of innovation strategy of industrial enterprise, Astra Saviness, Supplement, 2, 297.
    17. Zhu, D. H. and Chang, Y. P. (2014), Investigating consumer attitude and intention toward free trials of technology-based services, Computers in Human Behavior, 30, 328-334.
    18. Zuccato, A. (2007), Holistic security management framework applied in electronic commerce, Computers and Security, 26(3), 256-265.