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Browsing Phd by Author "Farhan Azmat Mir"

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    Role of multi-actors and digital service systems for value co-creation process
    (UMT Lahore, 2022-06-14) Farhan Azmat Mir
    Purpose: value co-creation is proving to be a game changing phenomenon for modern firms, yet many organizations are still following the traditional approach to value creation. A transition is required to actively involve key stakeholders in the process of generating overall value and creating memorable experiences. Research aims to understand how value co-creation takes place in complex service systems that comprise interactions between multiple human actors and digital service systems. Answering the question on how value is co-created, aims at providing clues to practitioners on how value co-creation initiatives could be managed within service systems. Exploration of the value co-creation process will also provide insights on required roles of human and digital service systems for sustainable value outcomes. Originality/value: empirical studies are rare in the context of value co-creation as evident from our systematic literature review; especially, context specific insights are warranted from the perspective of complex service system. Key aspects of value co-creation like antecedents, engagement patterns, application of resources, resource integration, and value outcomes need further exploration. Also, role of social influences and coordination mechanism on value co-creation requires exploration to provide explanation on their impact on value outcomes. Design/methodology/approach: thesis objectives and research questions warranted the use of a qualitative research approach. Where, empirical evidences were explored using case-study design. Three higher education institutions in NUST, VU and AIOU were explored to examine the value co-creation process. Choice of case studies were based on research objectives i.e. to examine value co-creation in a setting, where, human and digital service systems are playing active role in the process. Data came from a variety of sources to strengthen overall validity including observations, web page analysis and semi-structured interviews. Findings: nvivo 12 was used to extract codes from the transcripts and field notes and content analysis was used as a method to identify patterns within the data. Case findings revealed that HEIs represent useful examples of value co-creation. HEIs proved to be complex service systems as actors and digital service system were linked through an ever-evolving flux of service interactions. Value in context generated for any actor was dependent on other human actors and digital service system indicating the presence of a many-to-many value network. Evidence indicated that NUST and VU are generating value outcomes for their actors, enabling an overall coordination mechanism and service-based climate suitable for digitally enabled value co-creation. In contrast, actors within the network of AIOU are still getting familiarized to the evolving processes of value co-creation and would, rather, prefer face to face interaction over digital co-creation approach. Role of institutions, service climate, management support and awareness of value co-creation potential are few factors that proved to be critical for the success of value co-creation projects. Three simultaneous intervened dimensions of value co-creation are identified within complex XV service systems i.e. expedience, engagement and emergence. Human actors were found to play variety of roles based on their passive or active participation in the service process and beyond the processes; whereas, digital service systems were found to play facilitative and emergent roles within multiple dimensions of value co-creation. Four important management challenges in service, functional, complexity and viability are used to round off discussions and conclusions providing implications for managers. Research limitations: research findings from selected cases are used to provide context specific insights and lack of generalization was logically an inherent limitation. Although, there were similarities among cases, yet every case was unique in terms of its learning model and hence cross case analysis had its limitation as well.