Leveraging Technology Characteristics to Enhance Firm Customer Response Capability

Authors

  • Muhammad Imran Shah Qureshi Lahore Business School, University of Lahore, Pakistan.
  • Dr. Muhammad Arshad Lahore Business School, University of Lahore, Pakistan.

DOI:

https://doi.org/10.62019/yhnv1z35

Abstract

The purpose of this study is to investigate the impact of Technology Characteristics namely, reconfigurability and customization on Firm Customer Response Capability (CRC). A study conducted among the selected service sector organizations in Pakistan including Higher Education Institutions (HEIs) and Banking/ insurance companies investigates the relationship between technology characteristics and customer response capability. Drawing on data collected from 275 respondents in higher education and 283 from the banking sector, separate regression analyses were conducted to assess the relationship between technology characteristics and CRC. The findings show a strong positive relationship between technology characteristics and customer response capability. The study employed descriptive statistics, correlation analyses, and regression modeling, executed through SPSS, to examine the relationships among variables. The results underscore the critical role of technology characteristics in enhancing CRC in the service sector of Pakistan. Besides contributing to the theoretical literature on the relationship between technology characteristics and customer response capability, the results suggest service sector organizations to implement reconfigurable and customizable technologies which allow employees to tailor the system according to their workflows and specific task needs, leading to improved customer response capability. The findings of current study emphasize the tremendous and unexplored research potential at the intersection of information systems and other study disciplines, such as marketing and management. The findings offer practical implications for managers seeking to develop CRC of the firm by leveraging technology. Future studies could apply this framework across different organizational contexts and adopt diverse sampling approaches to strengthen the generalizability of the results.

References

Bala, H., & Venkatesh, V. (2013). Changes in employees' job characteristics during an enterprise system implementation: A latent growth modeling perspective. MIS quarterly, 1113-1140. DOI: https://doi.org/10.25300/MISQ/2013/37.4.06

Berraies, S., Chtioui, R., & Chaher, M. (2019). Customer-contact employees’ empowerment and customer performance: The CRM effectiveness as a mediator. International Journal of Productivity and Performance Management, 69(9), 1833-1859. DOI: https://doi.org/10.1108/IJPPM-07-2017-0169

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing Research, 18(1), 39-50. DOI: https://doi.org/10.1177/002224378101800104

Fu, J., Shang, R.-A., Jeyaraj, A., Sun, Y., & Hu, F. (2020). Interaction between task characteristics and technology affordances: task-technology fit and enterprise social media usage. Journal of Enterprise Information Management, 33(1), 1-22. DOI: https://doi.org/10.1108/JEIM-04-2019-0105

Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European business review, 31(1), 2-24. DOI: https://doi.org/10.1108/EBR-11-2018-0203

Homburg, C., Wieseke, J., & Bornemann, T. (2009). Implementing the marketing concept at the employee-customer interface: the role of customer need knowledge. Journal of marketing, 73(4), 64-81. DOI: https://doi.org/10.1509/jmkg.73.4.64

Huang, M.-H., & Rust, R. T. (2018). Artificial intelligence in service. Journal of Service Research, 21(2), 155-172. DOI: https://doi.org/10.1177/1094670517752459

Jayachandran, S., Hewett, K., & Kaufman, P. (2004). Customer response capability in a sense-and-respond era: The role of customer knowledge process. Journal of the Academy of Marketing Science, 32(3), 219-233. DOI: https://doi.org/10.1177/0092070304263334

Jayachandran, S., Sharma, S., Kaufman, P., & Raman, P. (2005). The role of relational information processes and technology use in customer relationship management. Journal of marketing, 69(4), 177-192. DOI: https://doi.org/10.1509/jmkg.2005.69.4.177

Junfeng, W., & Butkouskaya, V. (2025). Technology orientation, customer agility, customer performance: the moderating role of firm size in the Chinese tourism context. Asia Pacific Journal of Tourism Research, 1-16. DOI: https://doi.org/10.1080/10941665.2025.2454248

Lakshmi, U., & Jesiah, S. (2020). Literature Review on Customer Knowledge Management (CKM).

Larivière, B., Bowen, D., Andreassen, T. W., Kunz, W., Sirianni, N. J., Voss, C., Wünderlich, N. V., & De Keyser, A. (2017). “Service Encounter 2.0”: An investigation into the roles of technology, employees and customers. Journal of Business Research, 79, 238-246. DOI: https://doi.org/10.1016/j.jbusres.2017.03.008

Li, H., & Pan, Y. (2025). Exploring the impact of hedonic and utilitarian drivers of gamified learning in metaversity: A multi-group analysis. Education and Information Technologies, 1-36. DOI: https://doi.org/10.1007/s10639-024-13285-8

Nunnally, J. C. (1978). An overview of psychological measurement. Clinical diagnosis of mental disorders: A handbook, 97-146. DOI: https://doi.org/10.1007/978-1-4684-2490-4_4

Przegalinska, A., Triantoro, T., Kovbasiuk, A., Ciechanowski, L., Freeman, R. B., & Sowa, K. (2025). Collaborative AI in the workplace: Enhancing organizational performance through resource-based and task-technology fit perspectives. International Journal of Information Management, 81, 102853. DOI: https://doi.org/10.1016/j.ijinfomgt.2024.102853

Sajjaviriya, C., Jhundra-indra, P., & Boonlua, S. (2020). The Antecedents of Strategic Customer Response Capability: Empirical Evidence of Cosmetic Businesses in Thailand. Songklanakarin Journal of Management Sciences, 1-30.

Seddon, P. B., Calvert, C., & Yang, S. (2010). A multi-project model of key factors affecting organizational benefits from enterprise systems. MIS quarterly, 305-328. DOI: https://doi.org/10.2307/20721429

Setia, P., Setia, P., Venkatesh, V., & Joglekar, S. (2013). Leveraging digital technologies: How information quality leads to localized capabilities and customer service performance. MIS quarterly, 565-590.

Setia, P., & Venkatesh, V. (2013). Leveraging digital technologies: How information quality leads to localized capabilities and customer service performance. MIS quarterly, 565-590. DOI: https://doi.org/10.25300/MISQ/2013/37.2.11

Silva-Atencio, G. (2025). The Success of Customer-Centric Companies in the Global Context on the Road to Industry 5.0. Journal of Comprehensive Business Administration Research. DOI: https://doi.org/10.47852/bonviewJCBAR52024580

Stefan Thatcher, J. B., & Craig, K., Tams,. (2018). How and why trust matters in post-adoptive usage: The mediating roles of internal and external self-efficacy. The Journal of Strategic Information Systems, 27(2), 170-190. DOI: https://doi.org/10.1016/j.jsis.2017.07.004

Sukanthasirikul, K., & Phornlaphatrachakorn, K. (2021). Product innovation accounting, customer response capability and market success: An empirical investigation in Thailand. The Journal of Asian Finance, Economics and Business, 8(10), 65-76.

Sundaram, S., Schwarz, A., Jones, E., & Chin, W. W. (2007). Technology use on the front line: how information technology enhances individual performance. Journal of the Academy of Marketing Science, 35(1), 101-112. https://doi.org/10.1007/s11747-006-0010-4 DOI: https://doi.org/10.1007/s11747-006-0010-4

Tallon, P. P. (2007). A process-oriented perspective on the alignment of information technology and business strategy. Journal of Management Information Systems, 24(3), 227-268. DOI: https://doi.org/10.2753/MIS0742-1222240308

Trainor, K. J., Andzulis, J. M., Rapp, A., & 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. DOI: https://doi.org/10.1016/j.jbusres.2013.05.002

Tseng, H.-T. (2023). Customer-centered data power: Sensing and responding capability in big data analytics. Journal of Business Research, 158, 113689. DOI: https://doi.org/10.1016/j.jbusres.2023.113689

Tsou, H.-T. (2022). Linking customization capability with crm technology adoption and strategic alignment. Service Science, 14(1), 60-75. DOI: https://doi.org/10.1287/serv.2021.0286

Verhoef, P. C., Lemon, K. N., Parasuraman, A., Roggeveen, A., Tsiros, M., & Schlesinger, L. A. (2009). Customer experience creation: Determinants, dynamics and management strategies. Journal of retailing, 85(1), 31-41. DOI: https://doi.org/10.1016/j.jretai.2008.11.001

Wang, M., Zhao, D., & Gu, F. F. (2021). Distributors' customer-driving capability under supplier encroachment. Industrial Marketing Management, 94, 52-65. DOI: https://doi.org/10.1016/j.indmarman.2021.02.007

Wünderlich, N. V., Blut, M., Brock, C., Heirati, N., Jensen, M., Paluch, S., Rötzmeier-Keuper, J., & Tóth, Z. (2025). How to use emerging service technologies to enhance customer centricity in business-to-business contexts: A conceptual framework and research agenda. Journal of Business Research, 192, 115284. DOI: https://doi.org/10.1016/j.jbusres.2025.115284

Xu, M., Wang, W., Ou, C. X., & Song, B. (2023). Does IT matter for work meaningfulness?: Exploring the mediating role of job crafting. Information Technology & People, 36(1), 313-331.

Xu, M., Wang, W., Ou, C. X., Song, B., & People. (2022). Does IT matter for work meaningfulness?: Exploring the mediating role of job crafting. Information Technology & People. DOI: https://doi.org/10.1108/ITP-08-2020-0563

Yang, X. (2023). The effects of AI service quality and AI function-customer ability fit on customer's overall co-creation experience. Industrial Management & Data Systems, 123(6), 1717-1735. DOI: https://doi.org/10.1108/IMDS-08-2022-0500

Zulfiqar, S., Garavan, T., Huo, C., Akhtar, M. W., & Sarwar, B. (2025). Leaders’ knowledge hiding and front-line employee service sabotage. The Service Industries Journal, 45(2), 161-179. DOI: https://doi.org/10.1080/02642069.2023.2180499

Zvirgzdiņa, R., Liniņa, I., & Vēvere, V. (2015). Efficient consumer response (ECR) principles and their application in retail trade enterprises in Latvia. European Integration Studies(9), 257-264. DOI: https://doi.org/10.5755/j01.eis.0.9.12812

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Published

2025-08-21

How to Cite

Leveraging Technology Characteristics to Enhance Firm Customer Response Capability. (2025). The Asian Bulletin of Big Data Management , 5(3), 113-125. https://doi.org/10.62019/yhnv1z35