Search results

The purpose of this paper is to study whether just in time (JIT) supply practices interact with JIT production practices by positively moderating the relationship between JIT production and efficiency/delivery performance.

In total, six hypotheses are developed on the relationships between JIT production, JIT supply, efficiency and delivery performance. The hypotheses are tested through a hierarchical regression analysis using data from a sample of 207 manufacturing plants.

JIT production practices positively affect both efficiency and delivery. JIT supply practices positively moderate the relationship between JIT production and delivery, while there is no significant moderating effect when considering the impact on efficiency. The role of JIT supply as moderator is twofold. On the one hand, it strengthens the positive impact of JIT production on delivery through a complementary effect. On the other hand, low levels of adoption of JIT supply practices can hinder and – for extremely low levels – cancel the impact of JIT production practices on delivery.

When efficiency is the priority, companies should direct their efforts on JIT production. However, when their aim is to maximize delivery, they should invest on both JIT production and JIT supply. Results found advise managers to implement some JIT supply practices during the early stages of JIT production programs, because the total absence of any JIT linkages with suppliers can limit JIT production benefits on delivery performance.

This study elaborates on the mutual influence between JIT production and JIT supply practices and demonstrates that they have a different weight and contribute to different aspects of performance improvement. This can help managers involved in JIT implementation to better allocate scarce resources.

The purpose of this paper is to empirically investigate the effect of lean manufacturing on productivity changes and to identify the root sources of productivity changes. Furthermore, the authors explore the moderating effects of research and development (R&D) to examine the relationship between lean manufacturing and productivity changes.

This paper employs the propensity score matching (PSM) model combined with the difference-in-difference (DID) estimation to overcome the selectivity bias. The Malmquist productivity index is used to capture productivity changes. By analyzing 671 Chinese manufacturing listed firms from 2009 to 2014, the moderating effects of R&D on the relationship between lean manufacturing and productivity changes are measured.

The results reveal that lean manufacturing implementation has non-significant effects on productivity changes in principle, while a detailed analysis indicates that lean manufacturing could improve scale efficiency significantly. While engaged in R&D could significantly improve the efficiency of technological changes for lean manufacturing implementation firms, there exist negative effects on pure technical efficiency.

This research only covers manufacturing listed firms in China. Further studies should extend the generalizability of the findings.

This study helps managers to identify the important role of R&D on the relationship between lean manufacturing and productivity changes and provides insights into how to improve the lean manufacturing performance.

This paper appears to be one of the earliest studies on the relationship between lean manufacturing and productivity changes by applying the PSM combined with DID estimation in Chinese manufacturing environment.

Agricultural carbon productivity considers the dual goals of “agricultural economic growth” and “carbon emission reduction”. Improving agricultural carbon productivity is a requirement for promoting green and low-carbon development of agriculture. Agricultural production agglomeration is widespread worldwide, but the relationship between agricultural production agglomeration and agricultural carbon productivity is inconclusive. This paper aims to study the impact of agricultural production agglomeration on agricultural carbon productivity, which is conducive to a better understanding of the relationships among agglomeration, agricultural economic development and carbon emission, better planning of agricultural layout to build a modern agricultural industrial system and achieve the goal of carbon peaking and carbon neutrality.

Based on China's provincial data from 1991 to 2019, this paper uses non-radial directional distance function (NDDF) and Metafrontier Malmquist–Luenberger (MML) productivity index to measure total factor agricultural carbon productivity. Subsequently, using a panel two-way fixed effect model to study the effect and mechanism of agricultural production agglomeration on agricultural carbon productivity, and the two-stage least squares method (IV-2SLS) is used to solve endogeneity. Finally, this paper formulates a moderating effect model from the perspective of the efficiency of agricultural material capital inputs.

The empirical results identify that Chinese provincial agricultural carbon productivity has an overall growth trend and agricultural technological progress is the major source of growth. There is an inverted U-shaped relationship between agricultural production agglomeration and agricultural carbon productivity. The input efficiency of agricultural film, machine and water resources have moderating effects on the inverted U-shaped relationship. Agricultural production agglomeration also promotes agricultural carbon productivity by inhibiting agricultural carbon emissions in addition to affecting agricultural input factors and its internal mechanisms are agricultural green technology progress and rural human capital improvement.

This paper innovatively adopts the NDDF–MML method to measure the total factor agricultural carbon productivity more scientifically and accurately and solves the problems of ignoring group heterogeneity and the shortcomings of traditional productivity measurement in previous studies. This paper also explains the inverted U-shaped relationship between agricultural production agglomeration and agricultural carbon productivity theoretically and empirically. Furthermore, from the perspective of agricultural material capital input efficiency, this paper discusses the moderating effect of input efficiency of fertilizers, pesticides, agricultural film, agricultural machines and water resources on agricultural production agglomeration affecting agricultural carbon productivity and answers the mechanism of carbon emission reduction of agricultural production agglomeration.

Through the resource-based view (RBV) and contingency theory, this study empirically investigates the impacts of smart manufacturing systems' maturity levels on the performance of small and medium-sized enterprises (SMEs). Moreover, it aims to examine how industry types (i.e. high- and low-tech industries) and human-resource factors (i.e. the proportion of production workers to total workers) as contingency factors influence the effects of smart manufacturing systems.

The study conducted an empirical investigation of a sample of 163 Korean manufacturing SMEs. This study used an ordinary least squares regression to examine the impacts of the maturity levels of smart manufacturing systems on financial performance. Moreover, the impacts on operational efficiency were analysed using data envelopment analysis based on bootstrap methods and Tobit regression.

The RBV results indicate that the higher the maturity levels of smart manufacturing systems, the higher the financial performance and operational efficiency. Moreover, based on contingency theory, this study reveals that the effect of the maturity levels of smart manufacturing systems on financial performance and operational efficiency depends on firms' industry types and the proportion of production workers.

This study shows that the introduction of smart manufacturing systems can help SMEs achieve better financial performance and operational efficiency. However, their effectiveness is contingent on firms' industry types and the characteristics of their human resources.

Since the effects of the maturity levels of smart manufacturing systems on SME performance differ depending on their industries and the characteristics of human resources, managers need to consider them when introducing or investing in smart manufacturing systems.

Based on the RBV and contingency theory, this is the first empirical study to examine the moderating effects of industry types and the proportion of production workers on the impacts of the maturity levels of smart manufacturing systems on the financial performance and operational efficiency of SMEs.

This paper aims to intend to study the effect of movie production efficiency on eWOM and the moderating effect of efficiency on the relationship between eWOM and review helpfulness for movies.

Production efficiency is suggested by comparing the power of movie resources (e.g. the power of actors, directors, distributors, production companies) against box-office revenue through a data envelopment analysis (DEA).

The study results present that the number of reviews, the number of reviews by reviewers and review extremity are greater in an efficient subsample than in an inefficient subsample. For efficient movies, the review depth and the strength of the sentiments in the reviews are more positively related to review helpfulness. The prediction results for review helpfulness using the k-nearest neighbor method and automatic neural networks show that the efficient subsample provides a significantly lower prediction error rate than the inefficient subsample. The study results can support the effective facilitation of helpful online movie reviews.

As the numbers of online reviews are increasingly used to provide purchase decision support, it becomes crucial to understand which attributes represent average helpful reviews for movies. While previous studies have examined eWOM (online word-of-mouth) variables as predictors of helpfulness on movie websites, the role of the production efficiency of movies has not been examined considering the relationship between eWOM and review helpfulness for movies.

As a popular supply chain finance (SCF) strategy, reverse factoring has been widely adopted by buyer firms. However, the extant literature provides scant empirical evidence on the performance effect of reverse factoring. The purpose of this study is to seek to narrow this gap by empirically examining the relationship between reverse factoring and operating performance and the contingency conditions of this relationship.

Based on a sample of 167 announcements of reverse factoring implementation made by publicly listed Chinese manufacturing firms between 2014 and 2018, this paper employs a long-term event study approach to analyze the operating performance effect of reverse factoring as well as the moderating effects of production and innovation capabilities.

The event study results indicate that reverse factoring has a positive effect on buyer firms' operating performance in terms of cost efficiency and operating margin. In addition, both production and innovation capabilities positively moderate the relationship between reverse factoring and operating margin. However, neither of them moderates the relationship between reverse factoring and cost efficiency.

This is the first study that empirically examines the impact of reverse factoring on operating performance based on secondary data. Furthermore, it sheds light on the SCF literature by providing insights into the contingency effects of production and innovation capabilities, which also extends our understanding of the application of extended resource-based view in SCF research.

The purpose of this study is to demonstrate the nonlinear relationship between inventory stickiness and productivity, with investment efficiency being a mediator and environmental dynamism being a moderator.

Using a large panel data collected from 1,479 Chinese listed manufacturing enterprises over the period from 2010 to 2020, this research employs the instrumental variable method combined with two-stage least squares estimators to explore the inverted-U-shaped relationship between inventory stickiness and productivity. Furthermore, the mediating role of investment efficiency and the moderating role of environmental dynamism are demonstrated via two three-model systems.

As its core, productivity initially increases with inventory stickiness until a turning point at the end of the sample, beyond which the incremental effect of inventory stickiness on productivity become negative. That is, an inverted U-shaped relationship between inventory stickiness and productivity is found to exist. Moreover, further mediated moderation analysis highlights that investment efficiency is a key mediator of this relationship, whereas environmental dynamism is a key moderator.

Managers ought to gauge carefully against the tradeoffs between inventory stickiness and productivity. In general, over 90% of manufacturing enterprises have great potential to increase productivity by implementing sticky inventory management. In addition, managers are suggested to place emphasis on investment management and environmental strategy.

This paper contributes to the current understanding about productivity by illustrating and verifying the nonlinear effect of sticky inventory management. It may be the first study to empirically demonstrate the mediating effect of investment efficiency and the moderating effect of environmental dynamism on the relationship between inventory stickiness and productivity.

Short-term problem solving during production launch may result in extended lead times and increased overall costs of new product development, thereby reducing the overall profitability of a new product. While the previous literature suggests formalized procedures and systematic problem solving approaches, empirical analyses indicate improvised, non-systematic, and ad hoc responses actually being used in firms’ real world problem solving processes. The purpose of this paper is to explain the role of such non-systematic approaches for the efficiency and effectiveness of problem solving processes during production launch.

The paper empirically explores the impact of improvisational problem-solving behavior on a firm's production launch efficiency and on the success of new products. Moreover, the paper investigates the moderating role of technology familiarity, project complexity, and the number of occurring problems during production launch.

The paper finds evidence for a positive curvilinear effect of improvisational problem-solving behavior on new product success and production launch efficiency. Additionally, the paper finds that improvisation is especially reasonable in complex and familiar projects or in the case of many unplanned changes during production launch.

The study provides evidence for the relevance of routinized and improvisational behavior during production launch.

Improvisational behavior decreases the performance of the production launch and the financial performance of a new product in the case of frequent product changes or complex projects.

For the first time behavioral theory is applied to the phenomenon of production launch and problem solving.

This study aims to identify the relationship between different maintenance practices and productive efficiency in continuous process productive plants as well as the moderating effect of good training practices.

The empirical data were drawn from a database containing 609 observations of 29 productive units. Scales were validated using the Q-sort method. The panel data technique was used as the analysis methodology, with the inclusion of fixed effects for each productive plant.

Maintenance practices can effectively contribute to increasing the overall equipment effectiveness (OEE) of firms. Application of predictive maintenance practices should be considered as the primary training tool.

This study used a secondary database, limiting the research design and data manipulation.

The article provides practitioners with an analysis of maintenance practices by category (predictive, preventive and corrective), and the impact of each practice on the OEE of continuous process productive plants. Moreover, it explores the importance of training for extracting more results from maintenance practices.

Companies are investing in new technologies, but it is also essential to invest in training people. There is a demand for Industry 4.0 through the introduction of upskilling and reskilling programs.

This study used practice-based view (PBV) theory to explain how maintenance practices help firms achieve greater OEE. Furthermore, it introduced training practice as a moderating variable in the relationship between maintenance practices and OEE.

Farmers' adaptation strategies in agricultural production are required to minimise the negative impact of climate change on a nation's food production in developing countries. Based on the panel data of the provincial level in China from 2000 to 2017, this study aims to analyse the changing climate over recent years and farmers' adaptation strategy in terms of cropping in agricultural production.

This study uses Simpson's diversity index (SDI) to measure the degree of crop diversity planted by farmers and evaluate the influence of climate change on farmers' cropping strategy using the fixed-effect model. Further, the authors estimate the impact of farmers' cropping strategy on their economic performances in two aspects including yields and technical efficiency of crops.

The empirical results show that the overall climate appears a warming trend. Different from farmers in some other countries, Chinese farmers tend to adopt a more specialised cropping strategy which can significantly improve the technical efficiency and yields of crops in agriculture. In addition, as a moderating role, the specialised cropping can help farmers to alleviate the negative impact of climate change on technical efficiency of their crops.

First, previous studies showed that the changing climate influenced farmers' adaptation strategies, while most studies focussed on multiple adaptation strategies from the farm-level perspective rather than cropping strategy from the nation-level perspective. Second, the present study investigates how the cropping strategy affects the economic performance (in terms of the technical efficiency and crop yields) of agricultural production. Third, the stochastic frontier analysis method is used to estimate the technical efficiency. Fourth, this study explores the moderating effect between farmers' cropping strategy and technical efficiency by introducing an interaction item of SDI and accumulated temperature.