Interpretive Ranking of Choice of Interaction of Parent Firms Post-International Joint Venture Termination using TISM-IRP

Parameswar, Nakul; Dhir, Sanjay; Sushil, Sushil

doi:10.1007/s40171-019-00227-4

Cited by 19 publications

(10 citation statements)

References 104 publications

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“…Patil and Suresh (2019) have used TISM approach for modeling the enablers of workforce agility in Internet of things (IoT) projects. ISM-interpretive ranking process is used to study interpretive ranking of interactions of parent firm's post-international joint venture termination (Parameswar et al , 2020; Bamel et al , 2019).…”

Section: Methodsmentioning

confidence: 99%

An analysis of growth-accelerating factors for the Indian automotive industry using modified TISM

Meena

Dhir

Sushil

2020

IJPPM

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PurposeThis study aims to identify and prioritize various growth-accelerating factors in the Indian automotive industry. It further develops a hierarchical model to examine the mutual interactions between the factors, their dependence and their driving power.Design/methodology/approachThis study first identifies the growth-accelerating factors and then uses the modified total interpretive structural modeling (m-TISM) framework, which is an extended version of TISM. It further uses MICMAC analysis to analyze the mutual interrelation between the identified factors.FindingsThis study highlights the interrelation amongst the factors using m-TISM model. A hierarchical model shows the level of autonomous, dependence, linkage and independent factors considering the Indian automotive industry. This study also provides the understanding related to the interdependence of growth-accelerating factors.Research limitations/implicationsThe government and practitioners could evaluate the growth-accelerating factors which have higher driving power for implementing efficient policies and strategy formulation. By implementing m-TISM model in the Indian automotive industry, auto manufacturers can become more productive and profitable. Future studies could use other methods such as expert opinion to derive the factors, and further model could be verified using structural equation modeling technique.Originality/valueThis study uses a novel m-TISM framework for the analysis of growth-accelerating factors in the context of the Indian automotive industry. It further provides a detailed theoretical and conceptual understanding relating to the philosophy and establishes an interrelation amongst these under-researched growth-accelerating factors.

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Section: Methodsmentioning

confidence: 99%

An analysis of growth-accelerating factors for the Indian automotive industry using modified TISM

Meena

Dhir

Sushil

2020

IJPPM

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“…In this case, like a human brain, technology tends to solve the dilemma of decision making. It is easy to see that AI makes a major contribution to our everyday lives, in particular to entrepreneurs taking their marketing decisions during movement restrictions due to COVID-19 (Kim and Kim 2018 ; Sadiku-Dushi et al 2019 ; Parameswar et al 2020 ). Thus, we hypothesise that,…”

Section: Literature Review and Hypothesis Developmentmentioning

confidence: 99%

Technology and Entrepreneurial Marketing Decisions During COVID-19

Polas

Raju

2021

Glob J Flex Syst Manag

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The prime concern of this study is to explore how technology influences entrepreneurial marketing decisions during the world pandemic (COVID-19). The study uses a sample of 127 SMEs from Bangladesh. Data were collected by sending out questionnaires electronically and by mail. Smart PLS (SEM) 3.0 was used to analyse the data following the quantitative method. The study reveals positive and significant relationships between entrepreneurial opportunity recognition, opportunity development and opportunity exploitation with their entrepreneurial marketing decisions. It also claims that entrepreneurial passion mediates the relationship between entrepreneurial opportunity recognition and opportunity development with their entrepreneurial marketing decisions. However, entrepreneurial passion does not mediate the relationship between entrepreneurial opportunity exploitation and entrepreneurial marketing decisions. The study offers researchers a broader and more wide-ranging view of the importance of artificial intelligence in small firms. Researchers, educators and practitioners will benefit from the findings. The analyses are more complex and varied than the methodologies used in most of the limited previous research.

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“…comparisons are limited to a small set of 33 percent (Table 9) or 12 comparisons, which are further detailed for suggestions after discussion with the second set of experts (Sushil, 2017b(Sushil, , 2020Parmeshwar et al, 2020).…”

Section: Analysis and Findingsmentioning

confidence: 99%

Ranking the Factors Influencing e-Trading Usage in Agricultural Marketing

Chaudhary¹,

Suri

2021

Glob J Flex Syst Manag

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This research article attempts to rank the factors influencing continued e-Trading usage in Indian agriculture marketing. The ranking process is the first of its kind application in agricultural e-trading. A review of published literature has helped in identifying key factors influencing e-trading usage in agricultural marketing. The factors are ranked using the efficient Interpretive Ranking Process (IRP) methodology adopted in the context of agricultural marketing. Sixteen expert members, grouped into three different expert panels, have helped generate ranks and validation besides giving suggestions for improving e-trading usage in the context of the National Agriculture Market project (eNAM) in India. It has been found that the top factors influencing e-trading usage are 'Trust', 'Cost', 'Perceived Ease of Use', and 'Facilitating Conditions', respectively. These factors need to be supported with adequate resources to strengthen eNAM in terms of improved usage among the beneficiaries. It is further revealed that immediate attention is needed on aspects such as transparency, quick information dissemination, adequate quality assurance, uniformity in taxes and market fee, improvement in marketing infrastructure, inter-market trade logistics, conflict resolution, mobility and training.Further, the e-trading system's flexibility needs to be enhanced by incorporating modular design options, configurable new features, open-source innovation, cloud computing, and progressive artificial intelligence application.

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Interpretive Ranking of Choice of Interaction of Parent Firms Post-International Joint Venture Termination using TISM-IRP

Cited by 19 publications

References 104 publications

An analysis of growth-accelerating factors for the Indian automotive industry using modified TISM

An analysis of growth-accelerating factors for the Indian automotive industry using modified TISM

Technology and Entrepreneurial Marketing Decisions During COVID-19

Ranking the Factors Influencing e-Trading Usage in Agricultural Marketing

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