IT-based Knowledge, Adaptive Behavior and Service Performance Improvement

Zhuo Peng; Yu Wang

doi:doi:10.11648/j.ijiis.20211004.12

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IT-based Knowledge, Adaptive Behavior and Service Performance Improvement

Zhuo Peng, Yu Wang

Published in International Journal of Intelligent Information Systems (Volume 10, Issue 4)

Received: 26 July 2021 Accepted: 13 August 2021 Published: 24 August 2021

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Abstract

The continuing investment in IT applications in business operations by enterprises worldwide has generated interest and research among the academia pertaining to whether and how IT applications can enhance employees work performance. Within such a context, it is the objective of this paper to hypothesize and illustrate how service employees can utilize the IT-based knowledge to improve their service performance and achieve customer satisfaction. A model is developed based upon the literature of categorization and adaptive behavior, conceptualizing a IT-knowledge driven process in which employees categorize customers and adapt to them by modifying service delivery and customizing service options. Five hypotheses are thus proposed within the theoretical framework of this model to justify the causal relationship in-between IT-knowledge and service performance, mediated by employees’ adaptive behavior. It is argued in this paper that IT-based knowledge enables employees to assign the prospective customers to customers categories so as to anticipate their expectations and preferences. Accordingly, employees adjust their interpersonal behavior in their interactions with customers and customize service options to customers’ preferences. With the introduction of IT-based knowledge as an antecedent to adaptive behavior, this paper enriches the extant literature in IT support for employees performance and offers new insight to business management when motivating their service employees to elevate the level of customer satisfaction with the service quality.

Published in	International Journal of Intelligent Information Systems (Volume 10, Issue 4)
DOI	10.11648/j.ijiis.20211004.12
Page(s)	44-49
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

IT-based Knowledge, Service Performance, Adaptive Behavior, Categorization

References

[1]	Ahearne, M., Jelinek, R. and Rapp, A. (2004). Moving Beyond the Direct Effect of SFA Adoption on Salesperson Performance: Training and Support as Key Moderating Factors. Industrial Marketing Management, 34 (4), 379–388.
[2]	Ahearne, M., Jones, E., Rapp, A. and Mathieu, J. (2008). High Touch through High Tech: The Impact of Salesperson Technology Usage on Sales Performance via Mediating Mechanisms. Management Science, 54 (4), 671-685.
[3]	Benoit, S. (2010). Characteristics of Services – a New Approach Uncovers Their Value. Journal of Services Marketing, 24 (5), 359-368.
[4]	Bettencourt, L. A. and Gwinner, K. (1996). Customization of the Service Experience: The Role of the Frontline Employee. International Journal of Service Industry Management, 7 (2), 3–20.
[5]	Binning, J. F., Zaba, A. J. and Whattam, J. C. (1986). Explaining the Biasing Effects of Performance Cues in Terms of Cognitive Categorization. The Academy of Management Journal, 29 (3), 521-535.
[6]	Brady, M. K. and Cronin, J. (2001). Some New Thoughts on Conceptualizing Perceived Service Quality: A Hierarchical Approach. Journal of Marketing, 65 (3), 34–49.
[7]	Cascio, R., Mariadoss, B. J. and Mouri, N. (2009). The Impact of Management Commitment Alignment on Salespersons' Adoption of Sales Force Automation Technologies: An Empirical Investigation. Industrial Marketing Management 39 (7), 1088-1096.
[8]	Chen, R., Ou, X., Wang, W., Peng, Z. and Davison, R. M. (2020). Moving Beyond the Direct Impact of Using CRM Systems on Frontline Employees' Service Performance: The Mediating Role of Adaptive Behaviour. Information Systems Journal, 30 (3), 458-491.
[9]	Chirawattanakij, S. and Vathanophas, V. (2015). Knowledge Adoption: The influential Factors in the Process. Business Information Review, 32 (3), 158–167.
[10]	Cross, R., and Cummings, J. N. (2004). Tie and Network Correlates of Individual Performance in Knowledge Intensive Work. Academy of Management Journal, 47 (6), 928-937.
[11]	Davenport, T. H., Harris, J. G. and Kohli, A. K. (2001). How Do They Know Their Customers So Well?. MIT Sloan Management Review, 42 (2), 63-73.
[12]	Dous, M., Salomann, H., Kolbe, L. and Brenner, W. (2005). Knowledge Management Capabilities in CRM: Making Knowledge For, From and About Customers Work. Proceedings of the Eleventh Americas Conference on Information Systems, N. Romano (ed), Omaha, NE, USA, 167-178.
[13]	ElKordy, M. (2014). The Impact of CRM Capability Dimensions on Organizational Performance. European Journal of Business and Social Sciences, 10 (2), 128-146.
[14]	Evans, K. R., Kleine, R. E. III, Landry, T. D. and Crosby, L. A. (2000). How First Impressions of a Customer Impact Effectiveness in an Initial Sales Encounter. Journal of the Academy of Marketing Science, 28 (4), 512-526.
[15]	Garcia-Murillo, M. and Annabi, H. (2002). Customer Knowledge Management. Journal of the Operational Research Society, 53 (8), 875-884.
[16]	Gebert, H., Geib, M., Kolbe, L. M. and Brenner, W. (2003). Knowledge-enabled Customer Relationship Management. Journal of Knowledge Management, 7 (5), 107-123.
[17]	Gwinner, K. P., Bitner, M. J., Brown, S. W. and Kumar, A. (2005). Service Customization through Employee Adaptiveness. Journal of Service Research, 8 (2), 131-148.
[18]	Hsieh, J. J. Po-An., Rai, A., Petter, S. and Zhang, T. (2012). Impact of User Satisfaction with Mandated CRM Use on Employee Service Quality. MIS Quarterly, 36 (4), 1065–1080.
[19]	Huang, J. L., Ryan, A. M., Zabel, K. L. and Palmer, A. (2014). Personality and Adaptive Performance at Work: A Meta-analytic Investigation. Journal of Applied Psychology. 99 (1), 162–179.
[20]	Kelley, S. W. (1992). Developing Customer Orientation among Service Employees. Journal of the Academy of Marketing Science, 20 (1), 27-36.
[21]	McGarty, C. (1999). Categorization in Social Psychology, Thousand Oaks, United States: SAGE Publications Inc.
[22]	Min, J., Lee, J., Ryu, S. and Lee, H. (2014). Individuals' Interaction with Organizational Knowledge under Innovative and Affective Team Climates: A Multilevel Approach to Knowledge Adoption and Transformation. Proceedings of the 47th Hawaii International Conference on System Sciences. IEEE Computer Society, USA.
[23]	Motowidlo, S. J. and Kell, H. J. (2012). Job performance in; Schmitt, N. W. and Highhouse, S. (Eds) Handbook of psychology, vol. 12: Industrial and organizational psychology, 2nd Edition, Chichester: Wiley, 82-103.
[24]	Purcărea V. L., Gheorghe, I. R. and Petrescu, C. M. (2013). The Assessment of Perceived Service Quality of Public Health Care Services in Romania Using the SERVQUAL Scale. Procedia Economics and Finance, 6, 573-585.
[25]	Ramesh, K. (2014). Role of Customer Relationship Management in Indian Banking System. International Journal of Applied Services Marketing Perspectives, 4 (2), 645-650.
[26]	Rao, K. R. M. (2011). Services Marketing (2nd ed.), New Delhi, India: Dorling Kindersley.
[27]	Rapp, A., Agnihotri, R., and Forbes, L. P. (2008). The Sales Force Technology-Performance Chain: The Role of Adaptive Selling and Effort. Journal of Personal Selling & Sales Management, 28 (4), 335–350.
[28]	Robinson, L., Jr., Marshall, G. W., Moncrief, W. C. and Lassk, F. G. (2002). Toward a Shortened Measure of Adaptive Selling. Journal of Personal Selling & Sales Management, 22 (2), 111–119.
[29]	Román, S. and Iacobucci, D. (2010). Antecedents and Consequences of Adaptive Selling Confidence and Behavior: A dyadic Analysis of Salespeople and Their Customers. Journal of the Academy of Marketing Science, 38 (3), 363–382.
[30]	Sharma, A. and Levy, M. (1995). Categorization of Customers by Retail Salespeople. Journal of Retailing, 71 (1), 71-81.
[31]	Shen, A. and Ball, D. (2009). Is Personalization of Services Always a Good Thing? Exploring the Role of Technology-mediated Personalization (TMP) in Service Relationships. Journal of Services Marketing, 23 (2), 80-92.
[32]	Teigland, R. and Wasko, M. M. (2003). Integrating Knowledge through Information Trading: Examining the Relationship between Boundary Spanning Communication and Individual Performance. Decision Sciences, 34 (2), 261-286.
[33]	Teigland, R. and Wasko, M. M. (2009). Knowledge Transfer in MNCs: Examining How Intrinsic Motivations and Knowledge Sourcing Impact Individual Centrality and Performance. Journal of International management, 15 (1), 15-31.
[34]	Vergne, J. P. and Wry, T. (2014). Categorizing Categorization Research: Review, Integration, and Future Directions. Journal of Management Studies, 51 (1), 56-94.

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APA Style

Zhuo Peng, Yu Wang. (2021). IT-based Knowledge, Adaptive Behavior and Service Performance Improvement. International Journal of Intelligent Information Systems, 10(4), 44-49. https://doi.org/10.11648/j.ijiis.20211004.12

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ACS Style

Zhuo Peng; Yu Wang. IT-based Knowledge, Adaptive Behavior and Service Performance Improvement. Int. J. Intell. Inf. Syst. 2021, 10(4), 44-49. doi: 10.11648/j.ijiis.20211004.12

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AMA Style

Zhuo Peng, Yu Wang. IT-based Knowledge, Adaptive Behavior and Service Performance Improvement. Int J Intell Inf Syst. 2021;10(4):44-49. doi: 10.11648/j.ijiis.20211004.12

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@article{10.11648/j.ijiis.20211004.12,
  author = {Zhuo Peng and Yu Wang},
  title = {IT-based Knowledge, Adaptive Behavior and Service Performance Improvement},
  journal = {International Journal of Intelligent Information Systems},
  volume = {10},
  number = {4},
  pages = {44-49},
  doi = {10.11648/j.ijiis.20211004.12},
  url = {https://doi.org/10.11648/j.ijiis.20211004.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijiis.20211004.12},
  abstract = {The continuing investment in IT applications in business operations by enterprises worldwide has generated interest and research among the academia pertaining to whether and how IT applications can enhance employees work performance. Within such a context, it is the objective of this paper to hypothesize and illustrate how service employees can utilize the IT-based knowledge to improve their service performance and achieve customer satisfaction. A model is developed based upon the literature of categorization and adaptive behavior, conceptualizing a IT-knowledge driven process in which employees categorize customers and adapt to them by modifying service delivery and customizing service options. Five hypotheses are thus proposed within the theoretical framework of this model to justify the causal relationship in-between IT-knowledge and service performance, mediated by employees’ adaptive behavior. It is argued in this paper that IT-based knowledge enables employees to assign the prospective customers to customers categories so as to anticipate their expectations and preferences. Accordingly, employees adjust their interpersonal behavior in their interactions with customers and customize service options to customers’ preferences. With the introduction of IT-based knowledge as an antecedent to adaptive behavior, this paper enriches the extant literature in IT support for employees performance and offers new insight to business management when motivating their service employees to elevate the level of customer satisfaction with the service quality.},
 year = {2021}
}

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TY  - JOUR
T1  - IT-based Knowledge, Adaptive Behavior and Service Performance Improvement
AU  - Zhuo Peng
AU  - Yu Wang
Y1  - 2021/08/24
PY  - 2021
N1  - https://doi.org/10.11648/j.ijiis.20211004.12
DO  - 10.11648/j.ijiis.20211004.12
T2  - International Journal of Intelligent Information Systems
JF  - International Journal of Intelligent Information Systems
JO  - International Journal of Intelligent Information Systems
SP  - 44
EP  - 49
PB  - Science Publishing Group
SN  - 2328-7683
UR  - https://doi.org/10.11648/j.ijiis.20211004.12
AB  - The continuing investment in IT applications in business operations by enterprises worldwide has generated interest and research among the academia pertaining to whether and how IT applications can enhance employees work performance. Within such a context, it is the objective of this paper to hypothesize and illustrate how service employees can utilize the IT-based knowledge to improve their service performance and achieve customer satisfaction. A model is developed based upon the literature of categorization and adaptive behavior, conceptualizing a IT-knowledge driven process in which employees categorize customers and adapt to them by modifying service delivery and customizing service options. Five hypotheses are thus proposed within the theoretical framework of this model to justify the causal relationship in-between IT-knowledge and service performance, mediated by employees’ adaptive behavior. It is argued in this paper that IT-based knowledge enables employees to assign the prospective customers to customers categories so as to anticipate their expectations and preferences. Accordingly, employees adjust their interpersonal behavior in their interactions with customers and customize service options to customers’ preferences. With the introduction of IT-based knowledge as an antecedent to adaptive behavior, this paper enriches the extant literature in IT support for employees performance and offers new insight to business management when motivating their service employees to elevate the level of customer satisfaction with the service quality.
VL  - 10
IS  - 4
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Author Information

Zhuo Peng

School of Economics, Shenzhen Polytechnic, Shenzhen, China
Yu Wang

School of Economics, Shenzhen Polytechnic, Shenzhen, China

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APA Style

Zhuo Peng, Yu Wang. (2021). IT-based Knowledge, Adaptive Behavior and Service Performance Improvement. International Journal of Intelligent Information Systems, 10(4), 44-49. https://doi.org/10.11648/j.ijiis.20211004.12

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ACS Style

Zhuo Peng; Yu Wang. IT-based Knowledge, Adaptive Behavior and Service Performance Improvement. Int. J. Intell. Inf. Syst. 2021, 10(4), 44-49. doi: 10.11648/j.ijiis.20211004.12

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AMA Style

Zhuo Peng, Yu Wang. IT-based Knowledge, Adaptive Behavior and Service Performance Improvement. Int J Intell Inf Syst. 2021;10(4):44-49. doi: 10.11648/j.ijiis.20211004.12

Copy | Download

@article{10.11648/j.ijiis.20211004.12,
  author = {Zhuo Peng and Yu Wang},
  title = {IT-based Knowledge, Adaptive Behavior and Service Performance Improvement},
  journal = {International Journal of Intelligent Information Systems},
  volume = {10},
  number = {4},
  pages = {44-49},
  doi = {10.11648/j.ijiis.20211004.12},
  url = {https://doi.org/10.11648/j.ijiis.20211004.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijiis.20211004.12},
  abstract = {The continuing investment in IT applications in business operations by enterprises worldwide has generated interest and research among the academia pertaining to whether and how IT applications can enhance employees work performance. Within such a context, it is the objective of this paper to hypothesize and illustrate how service employees can utilize the IT-based knowledge to improve their service performance and achieve customer satisfaction. A model is developed based upon the literature of categorization and adaptive behavior, conceptualizing a IT-knowledge driven process in which employees categorize customers and adapt to them by modifying service delivery and customizing service options. Five hypotheses are thus proposed within the theoretical framework of this model to justify the causal relationship in-between IT-knowledge and service performance, mediated by employees’ adaptive behavior. It is argued in this paper that IT-based knowledge enables employees to assign the prospective customers to customers categories so as to anticipate their expectations and preferences. Accordingly, employees adjust their interpersonal behavior in their interactions with customers and customize service options to customers’ preferences. With the introduction of IT-based knowledge as an antecedent to adaptive behavior, this paper enriches the extant literature in IT support for employees performance and offers new insight to business management when motivating their service employees to elevate the level of customer satisfaction with the service quality.},
 year = {2021}
}

Copy | Download

TY  - JOUR
T1  - IT-based Knowledge, Adaptive Behavior and Service Performance Improvement
AU  - Zhuo Peng
AU  - Yu Wang
Y1  - 2021/08/24
PY  - 2021
N1  - https://doi.org/10.11648/j.ijiis.20211004.12
DO  - 10.11648/j.ijiis.20211004.12
T2  - International Journal of Intelligent Information Systems
JF  - International Journal of Intelligent Information Systems
JO  - International Journal of Intelligent Information Systems
SP  - 44
EP  - 49
PB  - Science Publishing Group
SN  - 2328-7683
UR  - https://doi.org/10.11648/j.ijiis.20211004.12
AB  - The continuing investment in IT applications in business operations by enterprises worldwide has generated interest and research among the academia pertaining to whether and how IT applications can enhance employees work performance. Within such a context, it is the objective of this paper to hypothesize and illustrate how service employees can utilize the IT-based knowledge to improve their service performance and achieve customer satisfaction. A model is developed based upon the literature of categorization and adaptive behavior, conceptualizing a IT-knowledge driven process in which employees categorize customers and adapt to them by modifying service delivery and customizing service options. Five hypotheses are thus proposed within the theoretical framework of this model to justify the causal relationship in-between IT-knowledge and service performance, mediated by employees’ adaptive behavior. It is argued in this paper that IT-based knowledge enables employees to assign the prospective customers to customers categories so as to anticipate their expectations and preferences. Accordingly, employees adjust their interpersonal behavior in their interactions with customers and customize service options to customers’ preferences. With the introduction of IT-based knowledge as an antecedent to adaptive behavior, this paper enriches the extant literature in IT support for employees performance and offers new insight to business management when motivating their service employees to elevate the level of customer satisfaction with the service quality.
VL  - 10
IS  - 4
ER  -

Copy | Download