To investigate the determinants of cloud computing adoption in the manufacturing micro, small and medium enterprises

Cloud adoption in Indian SMEs – an empirical analysis

Purpose

This study aims to empirically validate the determinants of cloud adoption in small and medium enterprises (SMEs) in India and examine its impact on their economic performance.

Design/methodology/approach

An integrated theoretical model interplaying technological, organizational and environmental aspects were applied for analyzing the variation in factors. Using data from 317 Indian SMEs, we have applied confirmatory factor analysis and structural equation modeling to test the hypotheses.

Findings

The results demonstrated that perceived usefulness, perceived ease of use, technology readiness, top management support and trust were the influencing drivers of cloud adoption in SMEs in India. Compared to previous studies, we did not find compatibility and competitive pressure as significant, suggesting that there was no single set of factors influencing technology adoption. Economic performance achieved by reduced transaction costs formed the basis of favorable adoption.

Research limitations/implications

The integrated model can provide space for new dimensions based on the category and geography of the SMEs. The paper does not address the supply-chain perspective of cloud adoption.

Practical implications

The study directs the firm owners to visualize business logic by creating a digital ecosystem. Further, the model guides the stakeholders, including cloud service providers, to contribute to the economic proficiency of the SMEs.

Originality/value

The paper empirically validates a model integrating both the drivers and consequences of cloud computing adoption as a unique study. Findings indicate that the usage of metrics such as return on investment and system efficiency form a part of the technology system approach.

Benchmarking the outsourcing factors of third-party logistics services selection: analysing influential strength and building a sustainable decision model

Purpose

Outsourcings always affect crucial supply chain functions concerning flexibility and cost. During the decision to outsource and consider third-party logistics service provider selection, decision-makers need to pay more attention to certain critical outsourcing factors such as coordination, integration and cooperation as these key factors are essential to improve overall supply chain performance. The main purpose of this work is to identify the inter-relations among outsourcing decision factors to highlight the most important and influential factors that should be considered and carefully thought through when making outsourcing sustainable decisions.

Design/methodology/approach

A two-phased methodology has been used in this study. In the first phase, outsourcing decision factors are identified from existing literature and validated by decision-makers from industry and academia. To understand the influential strength and build a sustainable model, the decision-making trial and evaluation laboratory method is used. A courier company in the UAE is considered for implementation.

Findings

All identified and validated factors are segregated into two categories (cause and effect). The result shows that the most influential factors are developing strategic alliances, uncertainty and risk mitigation and deficiency of internal resources for a service.

Practical implications

There are several insights for industry managers and practitioners. The results of the study may help practitioners and logistics managers to make the logistics service sustainable and more efficient for businesses.

Originality/value

This study focusses on a courier company to understand the interdependencies among outsourcing decision factors; this is unique in this field of literature.

Sustainable Supply Chain Management and Multi-Criteria Decision-Making Methods: A Systematic Review

Multi-criteria decision-making (MCDM) methods are smart tools to deal with numerous criteria in decision-making. These methods have been widely applied in the area of sustainable supply chain management (SSCM) because of their computational capabilities. This paper conducts a systematic literature review on MCDM methods applied in different areas of SSCM. From the literature search, a total of 106 published journal articles have been selected and analyzed. Both individual and integrated MCDM methods applied in SSCM are reviewed and summarized. In addition, contributions, methodological focuses, and findings of the reviewed articles are discussed. It is observed that MCDM methods are widely used for analyzing barriers, challenges, drivers, enablers, criteria, performances, and practices of SSCM. In recent years, studies have focused on integrating more than one MCDM method to highlight methodological contributions in SSCM; however, in the literature, limited research papers integrate multiple MCDM methods in the area of SSCM. Most of the published articles integrate only two MCDM methods, and integration with other methods, such as optimization and simulation techniques, is missing in the literature. This review paper contributes to the literature by analyzing existing research, identifying research gaps, and proposing new future research opportunities in the area of sustainable supply chain management applying MCDM methods.

Modelling human resource dimension of international project risk management

Purpose

Project risk management (PRM) and human resource management (HRM) are the two critical success factors (CSFs) for international project management. This paper aims to correlate these two CSFs, identify the human resource (HR) barriers, develop a hybrid model for risk management and develop strategies to overcome the HR barriers to effective risk management in international projects.

Design/methodology/approach

In total, 20 key HR barriers have been identified through a literature survey and verified by project professionals. These HR barriers are ranked according to their ability to trigger other barriers by analysing their interactions using the decision-making trial and evaluation laboratory (DEMATEL) method. Based on Ulrich’s revised model for HR functions, a hybrid framework for international PRM has been proposed.

Findings

DEMATEL analysis categorized nine barriers as cause barriers and 11 as affected barriers. The “PROJECTS” model proposed for HR strategy development suggests eight strategies to overcome these nine cause barriers. The hybrid PRM framework developed includes the effect of the HR dimension.

Research limitations/implications

This paper presents the generalized prioritization of HR barriers to international PRM. For a specific international project, the HR barriers and their prioritization may change slightly. The hybrid framework for PRM and the strategy development model suggested are yet to be validated.

Originality/value

Correlating two CSFs in international project management, i.e. HRM and PRM and ranking the HR barriers using the DEMATEL method is the uniqueness of this research paper. The hybrid framework developed for PRM based on HR functions in Ulrich’s revised model and the proposed new HR strategy development model “PROJECTS” are unique contributions of this paper.

An Integrated Decision-Making Model for Analyzing Key Performance Indicators in University Performance Management

University performance has an important effect on the social influence of universities. With increasing emphasis placed on higher education, it is important to improve and optimize university performance management. However, the performance of university management is affected by numerous indicators in practice, and it is difficult for administrators to optimize all of them because of resource restriction. To address this concern, in this paper, we design a novel integrated model by combining linguistic hesitant fuzzy sets (LHFSs) with the decision-making trial and evaluation laboratory (DEMATEL) method to identify key performance indicators (KPIs) for improving the level of university performance management. Specifically, the LHFSs are utilized to express the hesitant and vague interrelationship assessment of performance indicators provided by experts. A modified DEMATEL is adopted to visualize the causal relationship between performance indicators and determine critical ones. Moreover, we introduce a gray relation analysis (GRA)-based method to derive experts’ weights when their weight information is unknown. Finally, a comprehensive university in Shanghai, China, is employed as an example to illustrate the practicability and availability of the proposed linguistic hesitant fuzzy DEMATEL model.

Internet of things (IoT) based coordination system in Agri-food supply chain: development of an efficient framework using DEMATEL-ISM

Supply Chain Management (SCM) is one of the key aspects of making agriculture sector more competitive in India. India and other developing countries arefacing issues for coordination of their Agriculture Food Supply Chain Management (AFSCM) as not having technical and resources support; especially in natural disaster condition like recent COVID-19 outbreak. The purpose of this research is to develop anInternet of Things (IoT) based efficient and supportive coordinating system for enhancing the coordinating mechanism in AFSC under natural outbreaks. With the help of a literature review and experts’ inputs, seven enablers have been identified by grouping thirty sub enablers. Further, ISM methodology has been employed for developing a framework for enablers’ relationships to improve the coordination in the AFSC for taking strategic and operational decisions. After that, DEMATELtechnique is utilised to develop the causal and effectrelationships between all the identified enablers of a coordination system in IoT based AFSC. It has been noticed that‘Top Management Support (TMS)’ is the main driver by MICMAC analysis and categorised in a cause group based on (R-C) value. Further, the coordination index of the entire model is calculated based on the Cleveland theory. This paper also discussed a case study of the sugar mill industry. This paper also discussed stakeholder theory in developing IoT based coordination system of AFSC. Further, theoretical contribution may also guide the managers of the organisation in developing their strategies by using Strengths-Weaknesses-Opportunities-Threats (SWOT) analysis based on Cleveland index.

Applications of industry 4.0 to overcome the COVID-19 operational challenges

BACKGROUND AND AIMS

An epidemic outbreak of COVID-19 has increased the demand for medical equipment, medical accessories along with daily essentials for the safety of healthcare workers. This study aims to identify the operational challenges faced by retailers in providing efficient services. The study also aimed to propose the roadmap of Industry 4.0 to reduce the impact of COVID-19.

METHODS

A detailed literature review is done on an epidemic outbreak and supply chain using appropriate keywords on SCOPUS, Science Direct, Google Scholar. Some relevant industry reports and blogs are also taken to get insights.

RESULTS

We have identified twelve significant challenges for the retail sectors that are acting as operational barriers and provided the application of Industry 4.0 technologies to deal with it.

CONCLUSION

Industry 4.0 can act as a significant driver for reducing the impact of identified challenges on retailers to fight against the pandemic. There is a need to build trust and transparency for the effective management of healthcare essentials. The supply chain partners and government bodies should act wisely for improving the services during COVID-19 and of similar situations. The proposed roadmap provide future research directions for researchers working in the area of epidemic control, supply chain, and disaster management.

Quantifying SWOT analysis for cloud adoption using FAHP-DEMATEL approach: evidence from the manufacturing sector

Purpose

This study aims to identify the critical factors (barriers and drivers) influencing the adoption of cloud computing (ACC) in the manufacturing sector in India.

Design/methodology/approach

In this study, a mixed methodology approach is used. Interviews are conducted to investigate factors (drivers and barriers) influencing the ACC, which are further categorized as controllable determinants (weaknesses and strengths) and uncontrollable determinants (threats and opportunities) using a SWOT analysis. Fuzzy analytic hierarchy process (FAHP) has been utilized to highlight the most critical drivers as well as barriers. Finally, decision-making trial and evaluation laboratory (DEMATEL) has been used to find the cause-effect relationships among factors and their influence on the decision of adoption.

Findings

The manufacturing sector is in the digital and value change transformation phase with Industry 4.0, that is, the next industrial revolution. The 24 critical factors influencing ACC are subdivided into strengths, weaknesses, opportunities and threats. The FAHP analysis ranked time to market, competitive advantage, business agility, data confidentiality and lack of government policy standards as the most critical factors. The cause-effect relationships highlight that time to market is the most significant causal factor, and resistance to technology is the least significant effect factor. The results of the study elucidate that the strengths of ACC are appreciably more than its weaknesses.

Research limitations/implications

This study couples the technology acceptance model (TAM) with technology-organization-environment (TOE) framework and adds an economic perspective to examine the significant influences of ACC in the Indian manufacturing sector. Further, it contributes to the knowledge of ACC in general and provides valuable insights into interrelationships among factors influencing the decision and strategies of adoption in particular.

Originality/value

This is the first scholarly work in the Indian manufacturing sector that uses the analysis from SWOT and FAHP approach as a base for identifying cause-effect relationships between the critical factors influencing ACC. Further, based on the extant literature and analysis of this work, an adoption framework has been proposed that justifies that ACC is not just a technological challenge but is also an environmental, economic and organizational challenge that includes organizational issues, costs and need for adequate government policies.

Understanding cloud ERP continuance intention and individual performance: a TTF-driven perspective

Purpose

This study's purpose is to propose a hybrid model based on expectation-confirmation model (ECM) and technology acceptance model (TAM) to examine whether organizational users' perceived task-technology fit (TTF) in cloud enterprise resource planning (ERP) as an antecedent to user beliefs can directly and indirectly affect their continuance intention of cloud ERP and individual performance.

Design/methodology/approach

Sample data for this study were collected from end users of cloud ERP working in companies in Taiwan. A total of 500 questionnaires were distributed in the 50 sample companies, and 355 (71.0%) usable questionnaires were analyzed using structural equation modeling in this study.

Findings

This study showed that organizational users' perceived TTF contributed positively to their perceived usefulness, confirmation and perceived ease of use of cloud ERP, which in turn directly and indirectly led to their satisfaction with cloud ERP, continuance intention of cloud ERP and individual performance; that is, this study's findings strongly supported the research model integrating ECM, TAM and TTF model with all hypothesized links being significant.

Originality/value

This study contributes to an understanding of the TTF model in explaining organizational users' cloud ERP continuance intention that is difficult to explain with only their utilitarian perceptions of cloud ERP. Further, it is especially worth mentioning that this study places considerably more emphasis upon organizational users' individual performance greatly driven by their perceived TTF in cloud ERP and continuance intention of cloud ERP. Thus, this study's empirical evidence on incorporating ECM, TAM and TTF model can significantly enhance better understanding of the outcomes for cloud ERP continuance intention and shed light on the possible formulation of a richer post-adoption model.

Distributed manufacturing

Purpose

The purpose of this paper is to develop a preliminary conceptual scale for the measurement of distributed manufacturing (DM) capacity of manufacturing companies operating in rubber and plastic sectors.

Design/methodology/approach

A two-step research methodology is employed. In first step, the dimensions of DM and different levels of each dimension have been defined. In second step, an empirical analysis (cluster analysis) of database firms is performed by collecting the data of 38 firms operating in Italian mould manufacturing sector. Application case studies are then analyzed to show the use of the proposed DM conceptual scale.

Findings

A hyperspace, composed of five dimensions of DM, i.e. manufacturing localization; manufacturing technologies; customization and personalization; digitalization; and democratization of design, is developed and a hierarchy is defined by listing the levels of each dimension in an ascending order. Based on this hyperspace, a conceptual scale is proposed to measure the positioning of a generic company in the DM continuum.

Research limitations/implications

The empirical data are collected from Italian mould manufacturing companies operating in rubber and plastic sectors. It cannot be assumed that the industrial sectors in different parts of the world are operating under similar operational, regulatory and economic conditions. The results, therefore, might not be generalized to manufacturing companies operating in different countries (particularly developing countries) under different circumstances.

Originality/value

This is first preliminary scale of its kind to evaluate the positioning of companies with respect to their DM capacity. This scale is helpful for companies to compare their capacity with standard profiles and for decision making to convert the existing manufacturing operations into distributed operations.