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The purpose of this paper is twofold, first providing researchers with an overview about the uncertainties occurred in procurement including applicable approaches for analyzing different uncertain scenarios, and second proposing directions to inspire future research by identifying research gaps.

Papers related to supply chain risk management and procurement risk management (PRM) from 1995–2017 in several major databases are extracted by keywords and then further filtered based on the relevance to the topic, number of citations and publication year. A total of over 156 papers are selected. Definitions and current approaches related to procurement risks management are reviewed.

Five main risks in procurement process are identified. Apart from summarizing current strategies, suggestions are provided to facilitate strategy selection to handle procurement risks. Seven major future challenges and implications related PRM and different uncertainties are also indicated in this paper.

Procurement decisions making under uncertainty has attracted considerable attention from researchers and practitioners. Despite the increasing awareness for risk management for supply chain, no detail and holistic review paper studied on procurement uncertainty. Managing procurement risk not only need to mitigate the risk of price and lead time, but also need to have sophisticated analysis techniques in supply and demand uncertainty.

The contribution of this review paper is to discuss the implications of the research findings and provides insight about future research. A novel research framework is introduced as reference guide for researchers to apply innovative approach of operations research to resolve the procurements uncertainty problems.

Firms have been implementing lean manufacturing to improve their business performances. However, they have difficulties in the implementation due to the many barriers. In view of the lack of research and the importance in understanding them, the purpose of this paper is identify and evaluate the lean barriers with respect to their levels of importance in implementation.

As lean barriers are scattered in the literature and a variety of performance measures are used in practice, an extensive literature review is first carried out to identify the lean barriers and performance measures. A novel ranking technique – interpretive ranking process (IRP) – is adopted in the evaluation. In the IRP-based evaluation approach, a group discussion technique, where five Indian lean experts are involved, is applied to determine the most important lean barriers and performance measures. Several matrices are developed step by step for calculating the ranks of the selected lean barriers. Upon validating the ranks, an IRP-based lean barrier evaluation model is developed.

The IRP-based lean barrier evaluation model can help firms better understand lean barriers and their levels of importance in lean implementation. In the light of this model, to successfully implement lean, firms should provide sufficient management time and training to employees, develop a right culture, develop effective communication, carry out low-cost production, and obtain external funding.

The evaluation results provide the practitioners with a realistic framework to deal with many problems, especially those related to resource allocation, in lean implementation. Based on the framework, practitioners can prioritize lean barriers during implementation in accordance with performances targeted.

This is the first study that provides a comprehensive review of lean barriers available in the literature and evaluates them in accordance with performance measures. The combined use of literature review and experts in the evaluation approach justifies the value of the study.

The purpose of this paper is twofold. In view of the importance of process platform‐based production configuration (PPbPC) in sustaining product family production efficiency, it is to study the underlying logic for configuring production processes for a product family based on a process platform. Second, it is to apply the Petri nets (PNs) techniques to model PPbPC, in attempting to shed light on the underlying logic.

The authors first identify the fundamental issues in PPbPC, including variety handling, process variation accommodation, configuration at different abstraction levels, and constraint satisfaction. To accommodate the corresponding modelling difficulties, the authors develop a formalism of hierarchical colored timed PNs (HCTPNs) based on the principles of hierarchical PNs, timed PNs, and colored PNs. In the formalism, three types of nets together with a system of HCTPNs are defined to address the modelling of PPbPC.

Applying HCTPNs to vibration motors' case has revealed the logic of specifying complete production processes of final products at different levels of abstraction to achieve production configuration. The preliminary results also further demonstrate the feasibility of modelling PPbPC based on HCTPNs.

Traditional approaches to planning production processes for individual products may limit production performance improvement when companies need to timely produce a high variety of customized products. Systematic methods should be developed to plan production processes for product families so as to achieve production efficiency while utilizing the existing manufacturing resources.

By integrating the advantages of existing PN techniques, the HCTPNs formalism is developed to shed light on planning production processes for product families. The resulting production configuration model can facilitate practitioners to achieve production efficiency in producing large numbers of customized products.

The purpose of this paper is twofold. First, it is to introduce a knowledge‐based system for planning processes for families of final products, instead of component items, be they parts or assemblies. Second, it is to demonstrate the feasibility and potential of a prototypical system developed for planning processes families for truck families from a multinational company.

The authors first identify the challenges in planning process families, including data and knowledge representation and constraint handling. To accommodate these challenges, the paper adopts the integrated product and process structure (IP²S) and colored timed Petri nets (CTPNs) in the proposed knowledge‐based process family planning system. On top of the IP²S and CTPNs, XML‐based knowledge representation is employed to alleviate the difficulties in modelling complex product and process family data and planning knowledge while enabling information exchange across different operating platforms. In addition, in accordance with the correspondence between PNs and knowledge‐based systems, a mechanism is designed to cope with the generation of production rules, which model constraints.

The proposed system is able to automatically generate production processes for customized products. At a higher level, such production processes provide input (e.g. operations, machines) to downstream activities for planning process details to manufacture component parts or component assemblies.

Traditional trial and error approaches to planning processes limit production performance improvement when companies need to timely produce diverse customized products. Knowledge‐based systems should be developed to help companies better plan production processes based on the available manufacturing resources.

Unlike most reported studies addressing either detailed process planning or assembly planning for component parts or component assemblies, this study tackles process planning for final products, in attempting to maintain production efficiency from a holistic view.

The purpose of this paper is to provide a methodology to industry and academia on how to reengineer the order fulfillment process (OFP) by capitalizing on integration and coordination across the entire supply chain to sustain supply chain management.

A case study at a semiconductor equipment manufacturer in Singapore is undertaken.

This paper confirms that the traditional OFPs present companies a challenge to satisfy the demanding customer requirements while achieving performance optimization of each supply chain partner; and it is imperative to reengineer the OFPs to stay competitive. To successfully reengineer OFPs, the efforts should be systematically organized to, for example, exploit potential processes as many as possible, determine an optimal process based on mathematically sound grounds.

The use of a single case study may limit the generalizability of the findings.

A methodology incorporating accountability‐centered approach and simulation is developed for companies to reengineer OFPs while considering the entire supply chain.

The literature does not provide solutions for reengineering OFPs regardless of the fact that OFP reengineering is an emerging area of interest. This paper presents a valuable contribution to this topic by introducing a methodology and by applying the methodology to a semiconductor equipment manufacturer in Singapore.

The study critically evaluates the theory of International Financial Reporting Standards (IFRS) implementation in an attempt to provide directions for future research. Using the extensive structured review of literature using the Scopus database tool, the study reviewed 79 articles, and in particular the topic-related 57 articles were analysed. Nine journals contribute to 51% of articles (29 of 57 articles). In particular, the three journals published 15 articles: Critical Perspectives on Accounting (7), Accounting, Organizations and Society (4), and Journal of Applied Accounting Research (4). In total, 83% (47 of 57) of the articles were published 2009–2018. A total of 1,168 citations were found from 45 articles since 12 articles were without citations. The highest cited authors were Ball (2006) – 410 citations, Kothari, Ramanna, and Skinner (2010) – 135 citations, and Napier (1989) – 85 citations. In particular, five theories have been used widely: institutional theory (13), accounting theory (6), agency theory (3), positive accounting theory (3), and process theory (2). Future studies’ focus could be on theory implications in IFRS adoption/implementation studies in a country or a group of countries’ experience. Future studies could also focus on various theories rather depending on a single theory (i.e. institutional theory).

Social commerce (s-commerce) offers community-based platforms that facilitate customer-to-customer interactions and the development of customers' social shopping-based experience. While prior research has addressed the role of customer engagement (CE) in boosting s-commerce-based sales and performance, insight into the effect of s-commerce attributes on CE remains tenuous. Addressing this gap, this study examines the role of specific s-commerce attributes (i.e. community, collaboration, interactivity and social dynamics) on CE, which is, in turn, proposed to impact customers' repurchase- and electronic word of mouth (eWOM) intention.

A web-based survey was deployed to target users of a popular s-commerce platform, Etsy.com. Partial least squares structural equation modeling (PLS-SEM) was, then, used to analyze the survey data collected from 390 users.

The results reveal that the four examined attributes positively affect CE. The findings also demonstrate CE's positive effect on customers' repurchase- and eWOM intention.

Though CE has been identified as a key s-commerce performance indicator, little remains known about the role of specific s-commerce attributes in driving CE, as, therefore, explored in this research. Specifically, the authors examine the role of s-commerce-based community, collaboration, interactivity and social dynamics on CE. Their analyses also corroborate that CE, in turn, drives customers' post-purchase (i.e. repurchase/eWOM) intention. Managerially, our findings can be used to develop more engaging s-commerce platforms.

The purpose of this research is to examine the validity of the agriculture-induced environmental Kuznets curve (EKC) hypothesis with evidence from an autoregressive distributed lag (ARDL) approach with a structural break including real income and energy consumption in the model for Ghana over the period 1980–2014.

The ARDL approach with a structural break was used to analyze the agriculture-induced EKC model which has not been studied in Ghana. The dynamic ordinary least squares (DOLS), canonical cointegration regression (CCR) and fully modified ordinary least squares (FMOLS) econometric methods were further used to validate the robustness of the estimates, and the direction of the relationship between the study variables was also clarified using the Toda–Yamamoto Granger causality test.

The ARDL results revealed that GDP, energy consumption and agricultural value added have significant positive effects on CO₂ emissions, while GDP² reduces CO₂ emissions. The Toda-Yamamoto causality test results show a bidirectional causality running from GDP and energy consumption to CO₂ emissions whereas a unidirectional long-term causality runs from GDP² and agriculture value-added to CO₂ emissions.

This finding validated the presence of the agriculture-induced EKC hypothesis in Ghana in both the short run and long run, and the important role of agriculture and energy consumption in economic growth was confirmed by the respective bidirectional and unidirectional causal relationships between the two variables and GDP. Thus, a reduction in unsustainable agricultural practices is recommended through specific policies to strengthen institutional quality in Ghana for a paradigm shift from rudimentary technology to modern sustainable agrarian technologies.

This study is novel in the EKC literature in Ghana, as no study has yet been done on agriculture-induced EKC in Ghana, and the other EKC studies also failed to account for structural breaks which have been done by this study. This study further includes a causality analysis to examine the direction of the relationship which the few EKC studies in Ghana failed to address. Finally, dynamic ordinary least squares (DOLS), canonical cointegration regression (CCR) and fully modified ordinary least squares (FMOLS) methods are used for robustness check, unlike other studies with single methodologies.

Prefabricated housing has become a boom industry across the world; however, the uptake of offsite construction (OSC) approaches in Australian low-rise buildings is rather low compared with high-rise buildings in other countries. This study aims to investigate and analyse the adoption of different levels of OSC approaches and the selection of different procurement options in Australian low-rise residential buildings.

The research objectives were pursued through a mixed research method. An empirical questionnaire survey was carried out with 35 professionals in the Australian building and construction industry. Semi-structured interviews were conducted with 20 interviewees and analysed using thematic analysis method in NVivo software.

The research results found that the most suitable OSC level for Australian low-rise buildings is components-based prefabrication and identified the barriers to OSC uptake for each OSC level. The study also showed that the best option of procuring prefabricated products is from Australian manufacturers, followed by Australian suppliers/dealers and overseas manufacturers. Panelised prefabrication and components-based prefabrication are ranked as the most suitable OSC approaches for Australian manufacturers. Modular prefabrication is regarded as the most suitable for overseas manufacturer, while components-based prefabrication is the most suitable for Australian suppliers/dealers.

The selection of various OSC approaches and different procurement options in the low-rise residential buildings are scarcely explored topic, and thus, this study provides knowledge of interest for both researchers and practitioners.

While research on customer engagement and service innovation is rapidly emerging, limited insight exists into the interface of these topic areas. However, given the shared notion of (e.g. customer/firm) interactivity across these concepts, the purpose of this paper is to explore their theoretical interface that remains nebulous to date.

Building on a literature synthesis, the authors develop an S-D logic-informed “hamburger” model of service innovation that depicts the service innovation process, and its ensuing outcomes for particular actor groups, including the firm, its customers, etc. They conclude by proposing frontiers for future research that arise from the model.

The authors explore the theoretical foundations of customer engagement and service innovation, and integrate these in their S-D logic-informed “hamburger” model of service innovation. In the model, they acknowledge the key role of organizational resources in enabling service innovation, which will interact with specific service innovation actors (e.g. customers, employees) to create successful service innovations. The model next proposes service innovation development and implementation, from which focal service innovation actors will seek, and derive, particular types of value (e.g. profit for the actor of the firm), as shown at the top of the model. They conclude by offering a set of future research directions that arise from the model.

The S-D logic-informed “hamburger” model of service innovation can be used to guide future research into service innovation, including studies investigating service innovation’s role in driving customer engagement and value.

The attained insight will be useful to managers seeking to enhance their service innovation-based returns (e.g. by suggesting ways in which service innovation can enhance customer engagement).

The authors propose a novel, S-D logic-informed “hamburger” model of service innovation and its key antecedents (e.g. firm-based resources) and consequences (e.g. customer engagement and value).