More than ever companies are challenged to rethink their offerings while simultaneously being provided with a unique opportunity for creating or recreating their product-service systems. This paper ...seeks to address how servitisation can utilise the third wave of Internet development, referred to as the Internet of Things (IoT), which may unlock the potential for innovative product-service systems on an unprecedented scale. By providing an analysis of this technological breakthrough and the literature on servitisation, these concepts are combined to address the question of how organisations offering product-service systems can reap the benefits that the IoT. An analysis of three successful IoT implementation cases in manufacturing companies, representing different industry sectors such as metal processing, power generation and distribution, is provided. The results of the empirical research presented in the paper provide an insight into different ways of creating value in servitisation. The paper also proposes a framework that is aimed at proving a better understanding of how companies can create value, and add it to their servitisation processes with, the data obtained by the IoT based solutions. From the value chain perspective, IoT aided servitisation enables organisations to extend their value chains in order better serve their customers which, in turn, might result in increased profitability. The article proposes further research avenues, and offers valuable insight for practitioners.
•Internet of Things can enable possibilities of servitization for manufacturing companies.•Three case examples are analysed from value chain perspective.•IoT provides opportunity to access end-user operations and build service-products on data analytics.•A desired value chain positioning shift is toward downstream.
The effects of collaborative planning, forecasting and replenishment in the performance of supply chains have been discussed in the literature. In this research paper, we posit that these effects ...along with other collaborative factors influence the success of collaboration in supply chains. The objective of this paper is to uncover the impact of collaborative planning, collaborative decision making of supply chain partners and collaborative execution of all supply chain processes in the success of collaboration. We used empirical analysis to validate our research paradigm. Data were obtained through a questionnaire survey of customers of a Textile company. We used confirmatory factor analysis and structural equation modelling (using AMOS). The results of the analysis confirm that the factors of collaboration impact the success of supply chains that will lead to future collaborations. Collaborative execution of supply chain plans will also have an impact on future collaborations. Companies that are interested in supply chain collaborations can consider engaging in long-term collaboration depending on the success of current collaborations. This will help SC partners to make investment decisions particular to collaboration.
•Potential adoption barriers of Industry 4.0 are identified from the literature.•Industry experts validated the identified barriers and developed contextual relationships between them.•Relationships ...established among the barriers using ISM and Fuzzy MICMAC analysis.•Driving and dependence power of barriers in Indian manufacturing industry context is developed.•The results reveal the direct and indirect effects of identified barriers in the Industry 4.0 adoption.
The aim of this paper is the analysis of potential barriers which would hinder the manufacturing organizations from embracing Industry 4.0. This paper establishes relationships among the barriers using interpretive structural modeling (ISM) and finds out driving and dependence power of barriers, using fuzzy MICMAC (Matriced’ Impacts Croise´s Multiplication Applique´e a´ un Classement) analysis. A group of experts from industry and academia was consulted and ISM methodology was used to develop the contextual relationship among the identified barriers to Industry 4.0 adoption. The results of ISM were used as input to fuzzy MICMAC analysis for determining the driving and dependence power of the Industry 4.0 adoption barriers. The results are helpful in identifying and classifying the significant barriers, revealing the direct and indirect effects of each identified barrier on the Industry 4.0 adoption. The findings will help the practitioners and the policymakers for a detailed understanding of the Industry 4.0 adoption process and the barriers hindering its implementation. They may utilize the framework and the driving-dependence power of the barriers to understanding the inter-relationship between the barriers to building a valid and operative digital manufacturing platform. The study is first of its kind to identify industry 4.0 adoption barriers and develop hierarchical relationships between them using ISM and fuzzy MICMAC methodology in the Indian manufacturing context.
The lack of industrialization, inadequacy of the management, information inaccuracy, and inefficient supply chains are the significant issues in an agri-food supply chain. The proposed solutions to ...overcome these challenges should not only consider the way the food is produced but also take care of societal, environmental and economic concerns. There has been increasing use of emerging technologies in the agriculture supply chains. The internet of things, the blockchain, and big data technologies are potential enablers of sustainable agriculture supply chains. These technologies are driving the agricultural supply chain towards a digital supply chain environment that is data-driven. Realizing the significance of a data-driven sustainable agriculture supply chain we extracted and reviewed 84 academic journals from 2000 to 2017. The primary purpose of the review was to understand the level of analytics used (descriptive, predictive and prescriptive), sustainable agriculture supply chain objectives attained (social, environmental and economic), the supply chain processes from where the data is collected, and the supply chain resources deployed for the same. Based on the results of the review, we propose an application framework for the practitioners involved in the agri-food supply chain that identifies the supply chain visibility and supply chain resources as the main driving force for developing data analytics capability and achieving the sustainable performance. The framework will guide the practitioners to plan their investments to build a robust data-driven agri-food supply chain. Finally, we outline the future research directions and limitations of our study.
•Machine learning techniques enhance data-driven decision-making in agricultural supply chains.•Systematic literature review based on 93 papers on machine learning applications in agricultural supply ...chains.•Machine learning applications supports in developing sustainable agriculture supply chains.•A machine learning applications framework is proposed and related future perspectives are presented.
Agriculture plays an important role in sustaining all human activities. Major challenges such as overpopulation, competition for resources poses a threat to the food security of the planet. In order to tackle the ever-increasing complex problems in agricultural production systems, advancements in smart farming and precision agriculture offers important tools to address agricultural sustainability challenges. Data analytics hold the key to ensure future food security, food safety, and ecological sustainability. Disruptive information and communication technologies such as machine learning, big data analytics, cloud computing, and blockchain can address several problems such as productivity and yield improvement, water conservation, ensuring soil and plant health, and enhance environmental stewardship. The current study presents a systematic review of machine learning (ML) applications in agricultural supply chains (ASCs). Ninety three research papers were reviewed based on the applications of different ML algorithms in different phases of the ASCs. The study highlights how ASCs can benefit from ML techniques and lead to ASC sustainability. Based on the study findings an ML applications framework for sustainable ASC is proposed. The framework identifies the role of ML algorithms in providing real-time analytic insights for pro-active data-driven decision-making in the ASCs and provides the researchers, practitioners, and policymakers with guidelines on the successful management of ASCs for improved agricultural productivity and sustainability.
The recent interest in big data has led many companies to develop big data analytics capability (BDAC) in order to enhance firm performance (FPER). However, BDAC pays off for some companies but not ...for others. It appears that very few have achieved a big impact through big data. To address this challenge, this study proposes a BDAC model drawing on the resource-based theory (RBT) and the entanglement view of sociomaterialism. The findings show BDAC as a hierarchical model, which consists of three primary dimensions (i.e., management, technology, and talent capability) and 11 subdimensions (i.e., planning, investment, coordination, control, connectivity, compatibility, modularity, technology management knowledge, technical knowledge, business knowledge and relational knowledge). The findings from two Delphi studies and 152 online surveys of business analysts in the U.S. confirm the value of the entanglement conceptualization of the higher-order BDAC model and its impact on FPER. The results also illuminate the significant moderating impact of analytics capability–business strategy alignment on the BDAC–FPER relationship.
•We present a big data analytics capability (BDAC) model.•We frame BDAC on firm performance (FPER) using the RBV and the entanglement view of sociomaterialism.•We confirm the impact of BDAC on FPER and the role of business strategy alignment.
This article introduces the relationship between complexities and proactive management practices in supply chain resilience, particularly due to global sourcing (GS) strategies. The main objectives ...of this paper are as follows: (i) explain the various aspects of GS rather than reporting the trends and implications described in the literature, (ii) view GS in terms of complexity theory and (iii) investigate the resilience of supply chain due to GS complexity and suggest strategies to overcome complexities. We propose a GS resilience framework for future researchers to analyse the impact of GS complexity factors on supply chain resilience with respect to three outcomes: (i) risk and innovation, (ii) benefit in terms of sales promotion and (iii) challenges and responsiveness. Based on the framework, this introductory article summarises the papers appear in this special issue. This article would be useful to researchers and practitioners to further explore the role of complexities, proactive management strategies on GS resilience.
•Insights into the impact of COVID-19 outbreak on automobile and airline supply chain is provided.•Integrated time-to-recovery and financial impact analysis, empirical survey and semi-structured ...interviews were used.•Localized supply sources and industry 4.0 technologies identified as significant strategies by automobile industry.•Business continuity by defining operations at the airport and flights perceived significant strategy by airline industry.•Real-time information sharing and cooperation among supply chain stakeholders is critical.
There has been an increased interest among scholars to investigate supply chain resilience (SCRes) in manufacturing and service operations during emerging situations. Grounded in the SCRes theory, this study provides insights into the impact of the COVID-19 outbreak on the automobile and airline supply chain. Both the short and long-term response strategies adopted by the two supply chains are assessed, using a combination of qualitative and quantitative techniques in three distinct phases. In phase one, we use a sequential mixed-method for resilience evaluation, integrating Time-to-Recovery (TTR) and Financial Impact (FI) analysis. In phase two, we conduct an empirical survey involving 145 firms to evaluate the short-term SCRes response strategies. In the third phase, we conduct semi-structured interviews with supply chain executives both from the automobile and airline industries to understand the long-term SCRes response strategies. Our findings indicate that: (i) the automobile industry perceived that the best strategies to mitigate risks related to COVID-19, were to develop localized supply sources and use advanced industry 4.0 (I4.0) technologies. (ii) The airline industry on the other hand, perceived that the immediate need was to get ready for business continuity challenges posed by COVID-19, by defining their operations both at the airports and within the flights. (iii) Importantly, both the sectors perceived Big Data Analytics (BDA) to play a significant role by providing real-time information on various supply chain activities to overcome the challenges posed by COVID-19. (iv) Cooperation among supply chain stakeholders is perceived, as needed to overcome the challenges of the pandemic, and to accelerate the use of digital technologies.
The long-term viability of an organization hinges on social, environmental, and economic measures. However, based on extensive review of the literature, we have observed that measuring and improving ...the sustainable performance of supply chains is complex. We have grounded our theoretical framework in institutional theory and resource-based view and drawn thirteen hypotheses. We developed our instrument scientifically to validate our model and test our research hypotheses. The data was collected from the Indian auto components industry following Dillman’s total design test method. We gathered 205 usable responses. Following Peng and Lai’s (J Oper Manag 30(6):467–480,
2012
) arguments, we have tested our model using variance-based structural equation modeling (PLS-SEM). We found that the constructs used for building our theoretical model possess construct validity and further satisfy the specified criteria for goodness of fit. The hypotheses test further suggests that coercive pressures under the mediation effect of top management belief and participation have significant influence on resource selection (i.e. supply chain connectivity and supply chain information sharing). The supply chain connectivity and supply chain information sharing have significant influence on environmental performance. Contrary to our belief, the normative and mimetic pressures have no significant influence on top management participation. The managerial implications of the findings are also discussed.
Scholars acknowledge the importance of big data and predictive analytics (BDPA) in achieving business value and firm performance. However, the impact of BDPA assimilation on supply chain (SCP) and ...organizational performance (OP) has not been thoroughly investigated. To address this gap, this paper draws on resource-based view. It conceptualizes assimilation as a three stage process (acceptance, routinization, and assimilation) and identifies the influence of resources (connectivity and information sharing) under the mediation effect of top management commitment on big data assimilation (capability), SCP and OP. The findings suggest that connectivity and information sharing under the mediation effect of top management commitment are positively related to BDPA acceptance, which is positively related to BDPA assimilation under the mediation effect of BDPA routinization, and positively related to SCP and OP. Limitations and future research directions are provided.
PDF
