Towards Understanding the Cynicism of Social Networking Sites: An Operations Management Perspective

Jothimani, Dhanya; Bhadani, Abhay Kumar; Shankar, Ravi

doi:10.1016/j.sbspro.2015.03.206

Cited by 9 publications

(6 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…When there are number of variables involved in a system, the interactions among them can be analysed by two ways: direct relationship analysis and indirect relationship analysis using matrix multiplication properties (Jothimani et al, 2015). In direct relationship analysis, a direct relationship matrix "A" (Table VI) is obtained by considering the direct relationships in the final ISM.…”

Section: Micmac Analysismentioning

confidence: 99%

See 1 more Smart Citation

Analysis of barriers in implementation of digital transformation of supply chain using interpretive structural modelling approach

Agrawal

Narain

Ullah

2019

JM2

166

125

View full text Add to dashboard Cite

Purpose Digital supply chain (DSC) is an agile, customer-driven and productive way to develop different forms of returns for companies and to leverage efficient approaches with emerging techniques and data analytics. Though the advantages of digital supply chain management (DSCM) are many, its implementation is quite slow for several reasons. The purpose of this paper is to identify the major barriers which hinder the adoption of DSC and to analyse the interrelationship among them. The barriers of DSC are explored on the basis of existing literature and experts’ opinion. Design/methodology/approach This paper uses the interpretive structural modelling (ISM) approach to develop a hierarchical structural model which shows the mutual dependence among the barriers of DSC. Cross-impact matrix multiplication applied to classification analysis was performed to represent these barriers graphically on the basis of their driving power and dependence. Findings The research demonstrates that the barriers “no sense of urgency”, “lack of industry specific guidelines”, “lack of digital skills and talent” and “high implementation and running cost” are the most significant barriers to digital transformation of supply chain. This paper also suggests some managerial implications to overcome the barriers which hinder the implementation of digital transformation of supply chain. Practical implications This paper assists managers and policymakers to understand the order in which these barriers must be tackled and adopts a roadmap for successful implementation of DSCM and reap its benefits. Originality/value This is one of the initial research studies which has analysed the barriers of DSC using ISM approach.

show abstract

Section: Micmac Analysismentioning

confidence: 99%

“…Similarly, the matrix is multiplied n times to attain the interconnecting variables of nth order. When the rank of driving and dependence power reaches a stable state, the process gets terminated and completes the MICMAC analysis (Jothimani et al, 2015;Bhadani et al, 2016;Jothimani et al, 2016).…”

Section: Micmac Analysismentioning

confidence: 99%

Analysis of barriers in implementation of digital transformation of supply chain using interpretive structural modelling approach

Agrawal

Narain

Ullah

2019

JM2

166

125

View full text Add to dashboard Cite

show abstract

“…In the area of supply chain and logistics, studies have focused on supplier relationship [9] and selection [44], food SCM [24,25], e-procurement [72], and reverse logistics [14,62,84], among others. In the field of information technology studies are conducted in the areas of building information modeling [21,93], cloud computing [37,52], e-commerce security [19], m-commerce [96], enterprise resource planning [45], supply chain management [94], and social networking sites [95]. Energy domain studies were in the area of bio-diesel [68], smart grid technologies [60], and solar energy [79].…”

Section: Domain Of Studymentioning

confidence: 99%

“…Other studies have tried to explore different sets of variables. For example, article [84] has studied seven attributes of third party reverse logistics; article [39] has studied 17 motivational factors in the marketing area; article [44] has used 9 corporate social responsibility factors in the area supplier selection; article [85] has studied 25 SSCM practices; article [35] interrelated maintenance tools and technique; article [11] explored 13 psychological drivers of motivation in the area of green IT/IS; article [95] studied the interrelationships between 12 factors for abandoning social networking sites; article [29] studied capabilities and drivers for new product development; and article [30] studied 13 strategies for renewable energy. The number of variables being studied ranged from 5 [58] to 32 [20].…”

Section: Variables Of Studymentioning

confidence: 99%

SmartISM: Implementation and Assessment of Interpretive Structural Modeling

Ahmad

Qahmash

2021

Sustainability

View full text Add to dashboard Cite

Interpretive Structural Modeling (ISM) is a technique to establish the interrelationships between elements of interest in a specific domain through experts’ knowledge of the context of the elements. This technique has been applied in numerous domains and the list continues to grow due to its simplistic concept, while sustainability has taken the lead. The partially automated or manual application of this technique has been prone to errors as witnessed in the literature due to a series of mathematical steps of higher-order computing complexity. Therefore, this work proposes to develop an end-to-end graphical software, SmartISM, to implement ISM technique and MICMAC (Matrice d’Impacts Croisés Multiplication Appliquée á un Classement (cross-impact matrix multiplication applied to classification)), generally applied along with ISM to classify variables. Further, a scoping review has been conducted to study the applications of ISM in the previous studies using Denyer and Tranfield’s (2009) framework and newly developed SmartISM. For the development of SmartISM, Microsoft Excel software has been used, and relevant algorithms and VBA (Visual Basic for Applications) functions have been illustrated. For the transitivity calculation the Warshall algorithm has been used and a new algorithm reduced conical matrix has been introduced to remove edges while retaining the reachability of variables and structure of digraph in the final model. The scoping review results demonstrate 21 different domains such as sustainability, supply chain and logistics, information technology, energy, human resource, marketing, and operations among others; numerous types of constructs such as enablers, barriers, critical success factors, strategies, practices, among others, and their numbers varied from 5 to 32; number of decision makers ranged between 2 to 120 with a median value of 11, and belong to academia, industry, and/or government; and usage of multiple techniques of discourse and survey for decision making and data collection. Furthermore, the SmartISM reproduced results show that only 29 out of 77 studies selected have a correct application of ISM after discounting the generalized transitivity incorporation. The outcome of this work will help in more informed applications of this technique in newer domains and utilization of SmartISM to efficiently model the interrelationships among variables.

show abstract

“…The research databases show the exponential growth of the adoption of the ISM technique in diverse fields. It has been applied in many studies in the area of ICT [24][25][26] and very extensively in the area of sustainability. It has also been applied in the area of E-Learning [10,27].…”

Section: Introductionmentioning

confidence: 99%

Developing a Cloud-Based Mobile Learning Adoption Model to Promote Sustainable Education

2020

View full text Add to dashboard Cite

Education plays a very significant role in the context of sustainability. As the world population is growing, providing education through the traditional classroom setting is not sufficient and not feasible to extend learning in professional life. Therefore, modern technology-mediated learning paradigms such as mobile learning are becoming increasingly popular. Mobile learning is said to integrate multiple contexts, learning types, mobilities and communications. As information and communications technology (ICT) plays a vital role in the delivery of mobile learning services, it is very essential to adopt sustainable IT resources to keep it viable. Cloud computing offers a range of affordable, scalable and on-demand solutions. This paper attempts to model important critical success factors (CSFs) in the area of cloud-based mobile learning using the interpretive structural modeling (ISM) technique. ISM helps in identifying the hierarchical inter-relationships between the variables of study with the help of experts in the field. Finally, Matrice d’Impacts Croisés-Multiplication Appliquée á un Classement (MICMAC) analysis is employed to classify the variables into dependent and independent variables. Management support has been identified as most rudimentary among sixteen CSFs identified through a literature review to establish a distinguished relative advantage. Further, the paper discusses the theoretical underpinning of all the constructs. This study will help organizations to implement mobile learning in sustainable ways.

show abstract

Towards Understanding the Cynicism of Social Networking Sites: An Operations Management Perspective

Cited by 9 publications

References 24 publications

Analysis of barriers in implementation of digital transformation of supply chain using interpretive structural modelling approach

Analysis of barriers in implementation of digital transformation of supply chain using interpretive structural modelling approach

SmartISM: Implementation and Assessment of Interpretive Structural Modeling

Developing a Cloud-Based Mobile Learning Adoption Model to Promote Sustainable Education

Contact Info

Product

Resources

About