Design resilience in the fuzzy front end (FFE) context: an empirical examination

This study provides a detailed understanding of the flexibilities that affect performance of innovation projects in the fuzzy front end (FFE) stage. We use the ambidextrous theory approach along with theories on flexibility to propose key drivers of design resilience in innovation projects. A set of six in-depth case studies across a variety of contextual settings is used to investigate important sources of flexibilities that contribute to design resilience. The effects of different design flexibility on the firms’ design resilience are examined. Specifically, an in-depth examination of ‘within case’ trends suggested key design flexibilities to be further examined in the ‘across case’ analyses. Our findings provide valuable insights about the enabling design flexibilities and contextual effects of design resilience in the FFE stage of innovation projects. Based on the findings from the case studies, four sources of design flexibility emerged that vary in terms of their influence on design resilience: (1) iterative learning, (2) modularity, (3) engineering change management and (4) design reuse. Patterns from the ‘across case’ analyses were then used to isolate specific types of design flexibilities that are important for design resilience and organisational resilience. We also provide categorisation of these drivers of design resilience in the context of passive flexibility and active flexibility practices. One of the major contributions of the study is that it provides a detailed categorisation of design resilience in relation to organisational resilience.     

Social sustainable supplier evaluation and selection: a group decision-support approach

Organisational and managerial decisions are influenced by corporate sustainability pressures. Organisations need to consider economic, environmental and social sustainability dimensions in their decisions to become sustainable. Supply chain decisions play a distinct and critical role in organisational good and service outputs sustainability. Sustainable supplier selection influences the supply chain sustainability allowing many organisations to build competitive advantage. Within this context, the social sustainability dimension has received relatively minor investigation; with emphasis typically on economic and environmental sustainability. Neglecting social sustainability can have serious repercussions for organisational supply chains. This study proposes a social sustainability attribute decision framework to evaluate and select socially sustainable suppliers. A grey-based multi-criteria decision-support tool composed of the ‘best-worst method’ (BWM) and TODIM (TOmada de Decisão Interativa e Multicritério – in Portuguese ‘Interactive and Multicriteria Decision Making’) is introduced. A grey-BWM approach is used to determine social sustainability attribute weights, and a grey-TODIM method is utilised to rank suppliers. This process is completed in a group decision setting. A case study of an Iranian manufacturing company is used to exemplify the applicability and suitability of the proposed social sustainability decision framework. Managerial implications, limitations, and future research directions are introduced after the application of the model.     

Investing in lean manufacturing practices: an environmental and operational perspective

Lean manufacturing practices (LMPs) and corporate environmental sustainability are becoming inextricably linked. Throughout the lean and green debate, many organisations have recognised that LMPs have implications for their sustainable development and competitive positioning. Not only LMPs are complex on their own, but when perceived from an environmental sustainability perspective, the decision to implement an LMP can become even more intricate. Although general tools exist, the lack of effective decision-making tools to help in the implementation of LMPs with an environmental sustainability dimension is palpable. Thus, this study tackles the aforementioned decision problem by incorporating environmental and operational performance outcome expectations as these expectations are viewed in light of the ease of implementation of various LMPs. A novel multi-criteria decision-making (MCDM) model for evaluation of LMPs is developed in this respect. The model integrates a three-parameter interval grey number with rough set theory and the TODIM method. The model is run using empirical data from six manufacturing organisations. The findings facilitate the identification of a ‘locus of investments’ for a better selection of LMPs. The robustness of the decision support model developed is assessed through sensitivity analysis.     

Antecedents of implementation success in closed-loop supply chain: an empirical investigation

Implementation of closed-loop supply chain (CLSC) has gained increased consideration in the last few years owing to an increase in environmental concerns, product returns and scarcity of natural resources. It aids in improving environmental, economic and social performances. The purpose of this study is to examine the impact of CLSC critical success factors (CSFs) on performance outcomes. Firstly, CSFs and performance outcomes are extracted by conducting exploratory factor analysis using SPSS software. Then, the relationships between CLSC CSFs and performance outcomes are empirically tested by Partial Least Squares-Structural Equation Modelling (PLS-SEM) approach, using the data collected from 138 professionals working in remanufacturing, refurbishing and recycling operations in North American manufacturing organisations. Empirical analysis demonstrates that CSFs, ‘environmental concerns’, ‘sustainable production’ and ‘product design and collection’ have a significant positive effect on environmental performance. Results also validate the significant positive effect of CSFs, ‘demand and inventory management’ and ‘raw material prices’ on economic performance. In our knowledge, this is the first study that examines the impact of CLSC CSFs on performance outcomes. The results provide managers in manufacturing organisations with insights on most important CSFs that improve performance.     

Developing environmental and social performance: the role of suppliers’ sustainability and buyer–supplier trust

We explore how environmental and social performance of manufacturing firms can be improved as sustainable supply chain management (SSCM) develops and evolves within a firm from internal to external practices. Importantly, this study considers how key suppliers’ sustainability performance and buyer–supplier trust mediate and moderate such a development. A conceptual framework is developed which relies on resource-based theories and emerging empirical evidence. Then, partial least square methodology is applied on survey data from a sample of Italian manufacturing firms. Results show that manufacturing firms’ sustainability performance improves as SSCM develops; however, while internal practices have a direct impact on performance, the effect of external practices on a manufacturing firm’s sustainability performance is fully mediated by key suppliers’ sustainability performance. Yet, buyer–supplier trust significantly influences the scope of such gains. Since evidence suggests that manufacturing firms are still struggling with how to leverage supply chain innovation potential for sustainable development, this study provides a timely and valuable contribution.     

Sustainable manufacturing in Industry 4.0: an emerging research agenda

This systematic review intends to identify how sustainable manufacturing research is contributing to the development of the Industry 4.0 agenda and for a broader understanding about the links between the Industry 4.0 and Sustainable Manufacturing by mapping and summarising existing research efforts, identifying research agendas, as well as gaps and opportunities for research development. A conceptual framework formed by the principles and technological pillars of Industry 4.0, sustainable manufacturing scope, opportunities previously identified, and sustainability dimensions, guided analysis of 35 papers from 2008–2018, selected by a systematic approach. Bibliometrics data and social network analysis complement results identifying how research is being organised and its respective research agendas, relevant publications, and status of the research lifecycle. Results point to that the current research is aligned with the goals defined by different national industrial programs. There are, however, research gaps and opportunities for field development, becoming more mature and having a significant contribution to fully developing the agenda of Industry 4.0.     

The relevance of Industry 4.0 and its relationship with moving manufacturing out,back and staying at home

In view of the fact that Industry 4.0 is becoming increasingly essential, the implementation of Industry 4.0 technologies is believed to be an essential strategic component in further increasing the efficiency of manufacturing processes and in determining decisions concerning globalisation strategies. Thus, this paper provides an empirical analysis of the essential constructs of Industry 4.0, and drivers and barriers for Industry 4.0. The paper is based on 270 valid answers to a questionnaire-survey distributed among Danish manufacturers. Regression analyses were used to test the proposed hypotheses. The results of the analyses reveal that the identified drivers and barriers for Industry 4.0 have a positive impact on the perceived relevance of Industry 4.0 among companies. Furthermore, the analyses show that the perceived relevance of Industry 4.0 among companies has a positive impact on companies that have moved manufacturing back and on companies that have moved manufacturing out and back. Conversely, the perceived relevance of Industry 4.0 among companies has a negative impact on companies that have remained domestic. The perceived relevance of Industry 4.0 has no impact on companies that have moved manufacturing out. This research, in general, offers to both researchers and practitioners an increased consciousness concerning the relevant drivers and barriers for Industry 4.0 in decision processes about where to locate manufacturing.     

A supply chain sustainability innovation framework and evaluation methodology

Sustainability is hinged on innovation. The importance of sustainable innovation management in sustainable supply chain management (SSCM) cannot be underestimated. Studies on SSCM have emphasised the need for sustainable innovation in achieving sustainability but none provide deep insights into sustainable innovation management in SSCM implementation. This lack of research depth stimulates this study to identify and investigate criteria for sustainable supply chain management innovation advancement. This paper proposes a sustainable innovation criteria framework for investigating sustainable supply chains in manufacturing companies. To exemplify the applicability and efficiency of the proposed framework, a sample of five Indian manufacturing companies are used to evaluate and prioritise the sustainable innovation management criteria, using the ‘best–worst’ multi-criteria decision-making (BW-MCDM) model. The criteria weights for all companies from BWM are aggregated, averaged and used for ranking. The respondent managers viewed ‘financial availability for innovation’ as the most important sustainable innovation sub-criteria. The results of the study will inform industrial managers, practitioners and decision-makers on which criteria to focus on during the implementation stage, to increase sustainability in manufacturing supply chains, and further advance corporate and supply chain sustainable development. The framework may also serve as a theoretical construct for a future empirical study on sustainable supply chain innovation in the manufacturing sector. This paper sets the stage for further research in sustainable innovation practices in the manufacturing sector and its supply chains.     

Drivers and enablers of supplier sustainability practices: a survey-based analysis

A rich research stream investigates the drivers and enablers of supplier sustainability practices, usually classified into suppliers’ monitoring and collaboration with suppliers. Differently from previous works analysing relationships between supplier sustainability practices and drivers or enablers, this research investigates how well-defined configurations of monitoring and collaboration can be characterised in terms of drivers and enablers. In this way, it intends to advance knowledge by identifying what drivers and enablers are important and distinctive for the different configurations of supplier sustainability practices. A first result is that moving from configurations of plants which less adopt supplier sustainability practices (i.e. non-adopters) to those which invest on monitoring and/or collaboration to a limited extent (i.e. partial adopters) up to the most advanced ones (i.e. full-adopters), the pressure due to cost reduction lessens its relative importance as a driver, while the pressure due to regulations remains essential. Other relevant results are that plant size acts as a barrier for non-adopters, and the alignment between the sustainability project and plant goals results determinant especially for full-adopters. This research also enriches the debate on the opportunity of differentiating between supplier monitoring and collaboration when investigating drivers/enablers, providing evidence of the risk of oversimplifications for some enablers/drivers.     

The synergistic effect of environmental sustainability and corporate reputation on market value added (MVA) in manufacturing firms

This study is an attempt to explore the predictive effect, in terms of operational capability, of a large manufacturing firm’s environmental greening efforts carried out in the interest of sustainability, and of the firm’s reputation for social responsibility. Through both a traditional and a new, innovative approach, this study investigates the potential synergistic effect of environmental sustainability and the improvement of corporate reputation on a firm’s market performance in terms of shareholders’ equity value (market value added, or MVA) when taken together with the firm’s other key differential business factors. The findings of this study provide notable implications that establish the integrative paradigm for the influence of environmental greening sustainability on firm performance through the use of an innovative methodological approach regardless of a priori theoretical assumptions. Through this, the impact of environmental sustainability and corporate reputation, as well as their synergistic effect, on firm performance push forward a new foundation in business practice. The major findings and new methodological approach (Back-Propagation Neural Networks; BPNN) in this study will open a broad new spectrum of opportunities for further research on these topical issues.     

Relationship building,lean strategy and firm performance: an exploratory study in the automotive supplier industry

In contrast to previous literature, we propose that commitment to lean strategy should be preceded by building close relationships with key supply chain partners (suppliers and customers). Two aspects of lean strategy, lean manufacturing and lean design are studied in this paper. We hypothesize that relationship building positively affects both aspects of lean strategy, which in turn positively influences firm performance. To test these relationships, we use data from the top 150 auto suppliers to the ‘Big Three’ original equipment manufacturers (OEMs). The results show positive relationships between (1) relationship building and lean design, (2) relationship building and lean manufacturing, and (3) lean design and firm performance. This suggests that relationship building is more valuable for enhancing the ‘product’ aspects of lean strategy as opposed to the ‘process’ aspects of lean strategy. Process aspects of lean strategy appear to be largely a function of internal efforts.     

Impacts of Industry 4.0 technologies on Lean principles

Industry 4.0 is increasingly being promoted as the key to improving productivity, promoting economic growth and ensuring the sustainability of manufacturing companies. On the other hand, many companies have already partially or fully implemented principles and tools from the Lean management approach, which is also aimed at improving productivity. While the two approaches use very different strategies, they share some common principles. The objective of this article is to highlight the links between the principles and tools proposed by Industry 4.0 and those proposed by the Lean management approach, with a particular focus on how some of Industry 4.0's technologies are improving the implementation of Lean principles, depending on the technologies’ capability levels. As such, this study aims to provide a characterisation of the impacts of Industry 4.0 technologies on Lean principles according to targeted capability levels. The results obtained show strong support for Industry 4.0 technologies for Just-in-time and Jidoka, but little or no support for waste reduction and People and Team work. There is, therefore, a clear need to pursue the deployment of Lean management while improving certain Lean principles using Industry 4.0 technologies.     

Boosting sustainability and financial performance: the role of supply chain controversies

In recent years, numerous scandals concerning working conditions in Asia have threatened the reputation of large companies like Wal-Mart and Inditex. Since such scandals call attention to activities harmful to sustainable development, it is very important to study the relationships between concerns for sustainable supply chain management (SSCM), sustainability, and organisations’ market value. The added value of our study is, first, to explore SSCM controversies as drivers of or pressures for adopting and applying sustainability practices; and, second, to contribute to the recent but growing literature that analyses the channels through which SSCM and sustainability practices influence the firm’s value. We introduce sustainability environmental, social, and governance (ESG) practices as a mediator between SSCM controversies and market value to examine whether SSCM controversies with firms’ stakeholders lead to improvements in the ESG dimensions of organisational sustainability. We also examine the relationships between the ESG dimensions and market value, measured as Tobin’s Q ratio. The results confirm both the positive relationships of SSCM controversies to the ESG dimensions two years later and a positive relationship of the dimension of governance to Tobin’s Q. We also confirm a negative and significant relationship of the social dimension to Tobin’s Q, and a non-significant relationship of the environmental dimension to Tobin’s Q.     

An analytical technique to model and assess sustainable development index in manufacturing enterprises

Sustainable development (SD) will be the driving force to Twenty-first Century as automation was to the Twentieth Century and stream was to Nineteenth Century. There are two levels of sustainability: Macro-Level (country, cities) and Micro-Level (manufacturing enterprises and its town and regional areas). In this paper, Micro-Level of sustainability will be discussed. The major challenge of manufacturing enterprises is modelling and assessing the sustainable development performance. Introducing indexes for sustainable development assessment in manufacturing enterprises is important not only to enable them to quantitatively estimate SD, but also to determine the requirements of components for these enterprises to survive. The main objectives addressed in this paper is how to model the required components and how to introduce a new assessment framework for assessing sustainability from lowest levels, dimensions up to sustainable development level according to Micro-Level. The three pillars of sustainability (economic, social and environmental) are modelled, estimated and incorporated into a concept, the so-called ‘general sustainable development index’. Based on these concepts, the sustainable models will be analysed and presented through covering all aspects/issues of sustainability. The ultimate goal of this paper is considering the needs of manufacturing enterprise to be sustainable as well as to be globalised through introducing the concept of economic-social-environmental sustainable development and basic attitudes related to creating sustainable development value in engineering practices (economic), social (political) and environmental community. An industry-based case study is used to represent sustainability through aspects, performance metrics, indicators and pillars.     

Reconfiguring global pharmaceutical value networks through targeted technology interventions

Targeting a series of advanced manufacturing technology (AMT) ‘interventions’ provides the potential for significant step changes across the pharmaceutical value chain, from early stage ‘system discovery’ and clinical trials, through to novel service supply models. This research explores future value network configurations which, when aligned with disruptive shifts in technology (process and digital), may enable alternative routes to medicines production and the delivery of additional value to ‘end-users’, i.e. patients and health care providers. We draw on a categorisation of AMTs that may enable a shift from the traditional ‘batch’ and centralised manufacturing paradigm of ‘make-to-stock’, towards more re-distributed ‘continuous’ manufacturing and ‘make-to-order’ models. Despite reported benefits in the academic literature (e.g. reduced footprints, improved quality, enhanced flexibility and inventory savings), current adoption rates of continuous technologies in this sector remain low (c. 5%). This paper presents new data sources, in our study of AMT adoption in a global pharmaceutical context – assessing the barriers to implementation, and the pathways to delivering future continuous manufacturing scenarios. Our findings capture the high level of disparity in viewpoints, highlighting the uncertainties and transformational challenges ahead – in terms of opportunity areas, technological readiness and a future vision for the sector, as a whole.     

Fuzzy-based sustainable manufacturing assessment model for SMEs

Now-a-days, in the manufacturing, sustainability has become a necessity partly due to the threats created by traditional manufacturing practices, and due to regulations imposed by stakeholders. Sustainable manufacturing implies the creation of products that utilize minimum resources, has minimum negative impacts on environment and are safe for society at large at an affordable cost. This study proposes a fuzzy inference system-based model for the evaluation of manufacturing sustainability of small and medium enterprises (SMEs). In order to assess the manufacturing SMEs, decision makers’ opinion of the importance of sustainability measures and indicators and also the performance of enterprise with respect to indicators are gathered using linguistic variables. An illustrative list of sustainability indicators for manufacturing SMEs is identified considering the characteristics of SMEs. The implementation of our model for a manufacturing SME identified weak areas of performance which require appropriate strategy to enhance the overall sustainability. Based on the output of this assessment model and further deliberations with decision makers, case company is in process of selecting an appropriate strategy to reduce the environmental impacts. This model serves as a tool to assists the decision makers in assessing various dimensions of sustainability within their manufacturing SMEs.     

A Dynamic Maintenance Planning Framework Based on Fuzzy TOPSIS and FMEA: Application in an International Food Company

A maintenance planning framework is developed in this study to reduce and stabilize the maintenance costs of the manufacturing companies. The framework is based on fuzzy technique for order preference by similarity to ideal solution(TOPSIS) and failure mode and effects analysis (FMEA) techniques and supports maintenance planning decisions in a dynamic way. The proposed framework is general and can easily be adapted to a host of manufacturing environments in a variety of sectors. To determine the maintenance priorities of the machines, fuzzy TOPSIS technique is employed. In this regard, ‘risk priority number’ obtained by FMEA and ‘current technology’, ‘substitutability’, ‘capacity utilization’, and ‘contribution to profit’ are used as the criteria. Performance of the resulting maintenance plan is monitored, and maintenance priorities of the machines are updated by the framework. To confirm the viability of the proposed framework, a real‐world implementation in an international food company is presented. The results of the application reveal that the proposed maintenance planning framework can effectively and efficiently be used in practice. Copyright © 2015 John Wiley & Sons, Ltd.     

A study on investments in the big data-driven supply chain,performance measures and organisational performance in Indian retail 4.0 context

The use of digital technologies such as ‘internet of things’ and ‘big data analytics’ have transformed the traditional retail supply chains into data-driven retail supply chains referred to as ‘Retail 4.0.’ These big data-driven retail supply chains have the advantage of providing superior products and services and enhance the customers shopping experience. The retailing industry in India is highly competitive and eager to transform into the environment of retail 4.0. The literature on big data in the supply chain has mainly focused on the applications in manufacturing industries and therefore needs to be further investigated on how the big data-driven retail supply chains influence the supply chain performance. Therefore, this study investigates how the retailing 4.0 context in India is influencing the existing supply chain performance measures and what effect it has on the organisational performance. The findings of the study provide valuable insights for retail supply chain practitioners on planning BDA investments. Based on a survey of 380 respondents selected from retail organisations in India, this study uses governance structure as the moderating variable. Implications for managers and future research possibilities are presented.     

Human-centric,sustainability-driven approach to ranking smart cities worldwide

As cities worldwide adopt various high-tech solutions to solve emerging urban problems, transition toward greater smartness becomes a global trend. The question, however, remains how the cities’ progress towards greater smartness can be monitored and measured. Although different smart city (SC) classifications exist, these classifications are not always balanced, with some of them placing an emphasis on ICTs and infrastructure, while others prioritize social performance of cities and their physical environment. In this study, we suggest a relatively simple SC ranking system, based on two basic principles – direct relevance to human welfare and equal representation of key dimensions of sustainability. The proposed assessment system, composed of nine quantitative metrics, is applied to 100+ major cities worldwide, helping us to identify the best and the worst SC performers. As the study also reveals, there are clear regional differences in the interpretation components and underlying dimensions of SCs with an emphasis on “economy and technology” in North America, “the environment” in Europe, and “society” in Asia.