Analysing the adoption of cloud computing service: a systematic literature review

Learnings from Industry 4.0 for transitioning towards Industry 4.0+: challenges and solutions for Indian pharmaceutical sector

Industry 4.0 (I4.0) is helping production units to become smarter using cyber-physical systems and cognitive intelligence. The advanced diagnostics with I4.0 technologies (I4.0t) help in making the process highly flexible, resilient and autonomous. Still, the adoption of I4.0t especially in emerging economies like India is at a very slow pace. The present research has used an integrated approach i.e., Analytical Hierarchy Process-Combinative Distance-Based Assessment-Decision-Making Trial and Evaluation Laboratory to propose a barrier solution framework using data from pharmaceutical manufacturing sector. The findings reveal that "Costly venture" is found to be the most critical deterrent while "Customer awareness and satisfaction" is one of the potential solutions for I4.0t adoption. Further, lack of standardisation and fair benchmarking policies especially in the context of developing economies needs immediate attention. This article concludes by proposing a framework which will help to move from I4.0 towards Industry 4.0 + (I4.0+) which emphasises on role of collaboration between man and machine. And leads to sustainable supply chain management.

Possible Applications of Edge Computing in the Manufacturing Industry-Systematic Literature Review

This article presents the results of research with the main goal of identifying possible applications of edge computing (EC) in industry. This study used the methodology of systematic literature review and text mining analysis. The main findings showed that the primary goal of EC is to reduce the time required to transfer large amounts of data. With the ability to analyze data at the edge, it is possible to obtain immediate feedback and use it in the decision-making process. However, the implementation of EC requires investments not only in infrastructure, but also in the development of employee knowledge related to modern computing methods based on artificial intelligence. As the results of the analyses showed, great importance is also attached to energy consumption, both in ongoing production processes and for the purposes of data transmission and analysis. This paper also highlights problems related to quality management. Based on the analyses, we indicate further research directions for the application of edge computing and associated technologies that are required in the area of intelligent resource scheduling (for flexible production systems and autonomous systems), anomaly detection and resulting decision making, data analysis and transfer, knowledge management (for smart designing), and simulations (for autonomous systems).

Impact of COVID-19 pandemic on perishable food supply chain management: a contingent Resource-Based View (RBV) perspective

Purpose

This study investigates the impact of supplier visibility on the adoption of sustainable practices and supply chain performance. The paper applies contingent Resource-Based View to explain how information sharing with customers and suppliers and supply chain traceability has influenced visibility; visibility has impacted supply chain velocity sustainable practices, and finally, supply chain performance.

Design/methodology/approach

This research analyses 263 survey responses from UK retail (grocery) stores' executives and managers for perishable food during the COVID-19 pandemic.

Findings

The research results indicate that both supply chain traceability and information sharing (customers) positively influence visibility. Further, visibility positively influences the adoption of sustainable practices and velocity, positively impacting supply chain performance. However, information sharing with the customer has no significant influence on performance, and information sharing with the supplier has no significant relationship with visibility.

Originality/value

This research is the first attempt that explores the contingent Resource-Based View for the perishable food supply chain. Further, the empirical evidence provides meaningful insights for academics and industry by filling a crucial lacuna in the literature.

The Assessment of Big Data Adoption Readiness with a Technology–Organization–Environment Framework: A Perspective towards Healthcare Employees

Big data is rapidly being seen as a new frontier for improving organizational performance. However, it is still in its early phases of implementation in developing countries’ healthcare organizations. As data-driven insights become critical competitive advantages, it is critical to ascertain which elements influence an organization’s decision to adopt big data. The aim of this study is to propose and empirically test a theoretical framework based on technology–organization–environment (TOE) factors to identify the level of readiness of big data adoption in developing countries’ healthcare organizations. The framework empirically tested 302 Malaysian healthcare employees. The structural equation modeling was used to analyze the collected data. The results of the study demonstrated that technology, organization, and environment factors can significantly contribute towards big data adoption in healthcare organizations. However, the complexity of technology factors has shown less support for the notion. For technology practitioners, this study showed how to enhance big data adoption in healthcare organizations through TOE factors.

Assessment of Cloud Computing Success Factors for Sustainable Construction Industry: The Case of Nigeria

Cloud Computing has become a valuable platform for sustainability in many countries. This study evaluates the cloud computing implementation and its Critical Success Factors (CSFs) towards ensuring sustainable construction projects in Nigeria. Data were collected from previous literature, supplemented by a quantitative approach via a questionnaire survey. Data were collected from 104 construction professionals while cloud computing CSFs were examined using Relative Importance Ranking (RII) and Exploratory Factor Analysis (EFA). The results show that cloud computing’s awareness level is 96.2%, which means that the respondents are aware of cloud computing concept. Furthermore, the result shows that most of the respondents are adopting the concept. The analysis of the CSFs indicated that reliable data storage, performance as well as cost of accessibility and availability were the four most significant CSFs to cloud computing applications. Analysis of the CSFs through EFA generated four main components which include human satisfaction, organization, client’s acceptance, and industry-based. Consequently, this study contributed to existing body of knowledge by highlighting the cloud computing CSFs for achieving sustainable construction project. As such, the results could be a game-changer in the construction industry—not only in Nigeria but also in developing nations where construction projects are implemented through similar style and procedure. This study would be a benchmark for supporting decision-makers to improve data fragmentation, in which the use of data is paramount to the execution of construction works. Finally, the results of this study would be useful for enhancing sustainability and general management of construction projects through cloud computing implementation.

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.