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The exponential growth in the data collected in the form of electronic health records, registries, or wearable sensors has bought a big data revolution in the health industry. A large amount of information is required to be extracted from this substantially available data that provides numerous benefits such as improved quality of life, disease diagnosis, treatment and healthcare service delivery system. The big data generated in the healthcare is characterized by large volume, heterogeneity and speed. The other issues associated with the healthcare big data include non-uniform data, large number of variables, and need for real-time data analysis. In this paper, we examine the existing literature in all the databases within the ISI Web of Science with the purpose of reviewing the current research and develop a new agenda. Total 91 papers, classified in five research categories namely, general healthcare, clinical diagnosis and research, service delivery system, disease transmission and prevention, and health insurance were reviewed. Reviewing past work is focused on identifying areas where big data analytics (BDA) is being applied in healthcare management. The outcome of the review is a proposed framework on BDA capability and its impact on healthcare organization performance. [ABSTRACT FROM AUTHOR]

Dual cycling or double cycling (DC), is a strategy aimed at reducing the turnaround time for the vessel where the 'empty' moves of crane arm are used to carry a container thus causing the crane to be more productive. DC is acknowledged to increase capacity at ports, which will help the ports handle growth in container volumes in the near future. However, it is observed that Indian ports are reluctant to use this strategy. This study aims to explore and evaluate the implementation barriers for DC. A two-phase methodology was used. In phase one, fourteen implementation barriers were identified using an interview method. The second phase identified the most critical implementation barriers and their dependence using interpretive structural modeling (ISM). Ports information technology (IT) capability, and integration with other ports and stakeholders were identified as the top implementation barriers. [ABSTRACT FROM AUTHOR]

Highlights • Use of technology supports data-driven decision making in agriculture. • Big GIS is a potential IT processing tool for spatial data analysis and management. • A review of 120 papers on applications of big GIS in agriculture is presented. • There exists a vast potential for big GIS data in leveraging the food supply chains. • A big GIS analytics framework and future perspectives are presented. Abstract The world population is estimated to reach nine billion by 2050. Many challenges are adding pressure on the current agriculture supply chains that include shrinking land sizes, ever increasing demand for natural resources and environmental issues. The agriculture systems need a major transformation from the traditional practices to precision agriculture or smart farming practices to overcome these challenges. Geographic information system (GIS) is one such technology that pushes the current methods to precision agriculture. In this paper, we present a systematic literature review (SLR) of 120 research papers on various applications of big GIS analytics (BGA) in agriculture. The selected papers are classified into two broad categories; the level of analytics and GIS applications in agriculture. The GIS applications viz., land suitability, site search and selection, resource allocation, impact assessment, land allocation, and knowledge-based systems are considered in this study. The outcome of this study is a proposed BGA framework for agriculture supply chain. This framework identifies big data analytics to play a significant role in improving the quality of GIS application in agriculture and provides the researchers, practitioners, and policymakers with guidelines on the successful management of big GIS data for improved agricultural productivity. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to identify and model critical barriers to cloud computing adoption (CCA) in Indian MSMEs by the interpretive structural modeling (ISM) approach.Design/methodology/approach In this paper, through a literature survey and expert opinions, 14 critical barriers were identified, and the ISM tool was used to establish interrelationship among the identified barriers and to determine the key barriers having high driving power.Findings After analyzing the barriers, it was found that three barriers, namely, lack of confidentiality (B8), lack of top management support (B3) and lack of sharing and collaboration (B2) were most significant.Research limitations/implications The developed model is based on the expert opinions, which may be biased, influencing the final output of the structural model. The research implications of the developed model are to help managers of the organization in the understanding significance of the barriers and to prioritize or eliminate the same for the effective CCA.Originality/value This study is for the first time an attempt that has been made to apply the ISM methodology to explore the interdependencies among the critical barriers for Indian MSMEs. This paper will guide the managers at various levels of an organization for effective implementation of the cloud computing practices. [ABSTRACT FROM AUTHOR]

The evolution of digital platforms and related ecosystems has led to a new and essential context of entrepreneurship. Previous studies have revealed that although high-tech new ventures possess cutting-edge technology, they face significant challenges because of vital resource constraints and limited management capability. Design thinking practices have emerged as a prominent problem-solving approach offering innovation benefits during high uncertainties. However, in the context of high-tech ventures, more research is needed on linking the relationship between design thinking principles, innovation theories (effectuation and causation), and firm performance. The present study investigates how the design thinking principles influence innovation theories and whether it leads to improved high-tech venture performance. Based on a survey of 291 platform-based start-ups in India, the results show that design thinking ways are well integrated into the theories of effectuation and causation, facilitating the growth of platform-based ventures. However, the influence of effectuation and causation on platform-based venture performance is found to be mediated through the digital capabilities acquired by these ventures. • This study assesses how the design thinking principles influence innovation theories. • Digital capabilities (DCs) are critical in new platform-based ventures to drive performance. • DCs mediate between effectuation and causation's effect on venture performance. • Design thinking ways are well integrated into the theories of effectuation and causation. • Platform-based venture performance is affected by the experience of the entrepreneur. [ABSTRACT FROM AUTHOR]

Supply chain resilience (SCRes) and performance have become increasingly important in the wake of the recent supply chain disruptions caused by subsequent pandemics and crisis. Besides, the context of digitalization, integration, and globalization of the supply chain has raised an increasing awareness of advanced information processing techniques such as Artificial Intelligence (AI) in building SCRes and improving supply chain performance (SCP). The present study investigates the direct and indirect effects of AI, SCRes, and SCP under a context of dynamism and uncertainty of the supply chain. In doing so, we have conceptualized the use of AI in the supply chain on the organizational information processing theory (OIPT). The developed framework was evaluated using a structural equation modeling (SEM) approach. Survey data was collected from 279 firms representing different sizes, operating in various sectors, and countries. Our findings suggest that while AI has a direct impact on SCP in the short-term, it is recommended to exploit its information processing capabilities to build SCRes for long-lasting SCP. This study is among the first to provide empirical evidence on maximizing the benefits of AI capabilities to generate sustained SCP. The study could be further extended using a longitudinal investigation to explore more facets of the phenomenon. [ABSTRACT FROM AUTHOR]

The pulp and paper industry is critical to global industrial and economic development. Recently, India's pulp and paper industries have been facing severe competitive challenges. The challenges have impaired the environmental performance and resulted in the closure of several operations. Assessment and prediction of the performance of the Indian pulp and paper industry using various parameters is a critical task for researchers. This study proposes a framework for performance assessment and prediction based on Data Envelopment Analysis (DEA), Artificial Neural Networks, and Deep Learning (DL) to assist industry administration and decision-making. We presented a case study based on eight industries to demonstrate the methodology's applicability. This study analyses and predicts industry performance based on sample data observations over 30 years. The result suggests the DEA-DL-based efficiency prediction has an overall MSE of 0.08 compared with the actual efficiency. Furthermore, the efficiency rankings are compared between the three techniques. The results suggest that the integrated DEA-DL method is primarily accurate in most scenarios with the actual values. The findings of this study provide a comprehensive analysis of environmental performance for policymakers. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to examine the relationships between supplier development practices (SDPs) and supplier-buyer relationship practices from the supplier’s perspective (SBRSP), and seek to understand how specific SDPs may impact a buyer’s operational performance as well as supplier-buyer relationship practices.Design/methodology/approach The authors conducted a survey of 512 respondents from the different manufacturing firms in India and applied structural equation modelling to test a structural model that proposes the impacts of various efforts of SDPs on a buyer’s performance as well as SBRSP.Findings The study concludes that SDPs and SBRSP together improve the relationship between a buyer and supplier, and this improved relationship leads to competitive advantages (CAs) followed by profitability. Results indicate that supplier perspective of buyer-supplier relationship can be improved under the condition of SDPs and SBRSP together. SDPs are driven by productive measure and competitive pressure, whereas customer uncertainty is found to be statistically insignificant.Research limitations/implications The study was carried out in North Maharashtra Industrial Zone of India, where the auto sector and machine/components manufacturing firms have been established for a considerable period of time. Results of the study are limited to manufacturing organizations predominantly focussing on the automobile sector and machine/components manufacturing firms.Practical implications This study provides significant insights into the specific impact of various SDPs and SBRSP for both academics and practitioners. SDPs along with SBRSP practices lead to improvement in the relationship leading to CAs. SBRSP suggests that trust, long-term commitments and the supplier’s perspective are important practices for relationship improvement.Originality/value The current study attempts to identify what are the success factors for the supplier-buyer relationship from the supplier’s perspective and SDPs and how the supplier-buyer relationship can be improved under the condition of SDPs and SBRSP. Hence, the aim is to develop a more thorough understanding of the outcomes of a supplier-buyer relationship improvement from both buyer’s and supplier’s perspective, under the conditions of supplier development to achieve CAs leading to profitability. Furthermore, the study analyses the effect of the improved supplier-buyer relationship for achieving CAs leading to profitability. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to propose a framework for evaluating and selecting the most optimal third-party logistics (3PL) service provider vendor among the available ones. Selection is done based on the performance values of the vendors on certain predefined criteria.Design/methodology/approach An integrated approach involving data envelopment analysis (DEA), technique for order of preference by similarity to ideal solution (TOPSIS) and linear programming (LP) problem has been used to develop a new model for the selection of 3PL vendor. First, DEA is used to evaluate the efficiency of each vendor according to the identified criteria. Second, TOPSIS is applied to rank the maximally efficient vendors. Finally, LP problem is stated and solved to ascertain the quantities to be allocated to each maximally efficient vendor in the context of multiple logistics provider. The proposed DEA–TOPSIS–LP (DETOLP) model is finally tested with real-time industry data for 3PL vendor evaluation and selection. The study, thus, proposes a three-step hierarchical technique for selection of 3PL vendor based on the multiple criteria decision-making approach.Findings The paper focuses on assessing the performance of 26 vendors using a combined approach of DEA, TOPSIS and LP. It is observed that vendor V4 outperforms all the considered vendors, which exactly corroborates with the present scenario within the company.Research limitations/implications Exclusion of qualitative criteria for 3PL vendor selection and the judgment of weights for TOPSIS can be considered as the limitations of the present work. The study has significant practical implications for organizations belonging to any sector or industry. It can help them in evaluating the existing 3PL vendors and selecting the most efficient among them.Originality/value This paper deals with a framework modeled for 3PL vendor selection. It is the first attempt to utilize an integrated approach, i.e. DETOLP model for evaluation and selection of 3PL. For assessment of the model, real data from an Indian company has been taken to analyze the result and compare it with the present scenario within the company. [ABSTRACT FROM AUTHOR]

Telecommunication market in India is galloping with lightening speed. In spite of its swift growth trajectory and huge size of the projected market, the players in this space are experiencing difficulty in coping up with competitive pressures. To survive and to flourish in this arena, the marketers have no choice but to design and execute superior strategies. Conventional approach based on gut feel and common sense, is to be replaced by the strategies of sophisticated kind which are based on sound principles of established theories. This study aims at identifying the criteria used by the consumers while buying mobile handsets and ascertaining the weightage for each of them. Using the framework of Original Fishbein Model (Multi Attribute Attitude Model), the study analyses the attitude of the buyers towards prominent brands in the market and its relationship with choice decision. The output of this study is believed to be of value for the practicing marketer and academic in the area of Marketing and Consumer behaviour. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to investigate the relationship between two major constructs (supply chain management practices (SCMP) and supply chain performance measures), which determines the efficiency and efficacy of retail-supply chain management, using a rigorous empirical method to validate the instrument scale for measuring the validity and reliability of the identified constructs. Additionally, the paper further tests the relationship between SCMP and supply chain performance measures using structural equation modeling (SEM).Design/methodology/approach Data were compiled and collected from 213 operations and supply chain (SC) heads from leading retail stores in India. Confirmatory factor analysis was used to test the validity of the proposed measurement scale and the relationship is tested using SEM.Findings The results of the research will help the decision makers in the SC/procurement field to understand the importance of the association between SCMP and supply chain performance measures. Statistical tests show that the implementation of SCMP are associated with supply chain performance measures, which leads to overall improvements; moreover, there is a statistically significant association between the five SCMP and eight SCPM.Research limitations/implications This research is also needed to provide more understanding about the SCMP along with the supply chain performance measures and the positive association among them. Overall, this research provides an additional insight into the growing field of the relationships between SCMP and SCPM. Clearly, the field has ample space to grow in terms of research and practice.Originality/value This research paper contributes to the literature on supply chain performance measurement. [ABSTRACT FROM AUTHOR]