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This study aims to examine the complex effects of foreign direct investment (FDI) on China’s agricultural total factor productivity (TFP) from 2005 to 2020. It also explores the role of absorptive capacity as a moderating factor during this period.

Employing provincial panel data from China, this research measures agricultural TFP using the Stochastic Frontier Approach (SFA)-Malmquist method. The impact of FDI on agricultural productivity is further analyzed using a nondynamic panel threshold model.

The results highlight technological progress as the main driver of agricultural TFP growth in China. Agricultural FDI (AFDI) seems to impede TFP development, whereas nonagricultural FDI (NAFDI) shows a distinct positive spillover effect. The study reveals a threshold in absorptive capacity that affects both the direct and spillover impacts of FDI. Provinces with higher absorptive capacity are less negatively impacted by AFDI and more likely to benefit from FDI spillovers (FDISs).

This study provides new insights into the intricate relationship between FDI, absorptive capacity and agricultural productivity. It underscores the importance of optimizing technological progress and research and development (R&D) to enhance agricultural productivity in China.

The productivity of a port is a measure that is important to different stakeholders: port administrators (port authority), third-party logistics providers, manufacturers and consumers, among others. This study analyses productivity in terms of vessel movement efficiencies (loading/unloading of cargo) and container release from port facilities. Both factors add to the overall productivity in any port.

A comparative analysis of the productivity of three ports is measured using a Quality Function Deployment (QFD) and benchmarking analysis to help establish strategies that will help improve productivity. Considering the information confidentially the authors will call the ports according to their geographic location. The ports under study are the USA Southeast Port (Port of America), Central Asian Port (Port of Asia) and Central Europe Port (Port of Europe).

This study has established an analysis strategy that allows seeing points of sale in the ports. This study will compare three different continents, only to demonstrate the applicability of QFD and benchmarking. Still, the strategy can be used in ports that compete due to their proximity and location. Identifying the variables to be analyzed made it possible to establish a strategy to increase productivity.

There are many studies that analyze port productivity, but none try to standardize the variables to be compared in different scenarios. This study has compared three ports from three different geographical areas, using the same variables in all three cases. The study critically analyses the performance of three ports and proposes a strategy based on QFD and benchmarking research.

This paper aims to examine the impact of six possible foreign direct investment (FDI) spillover channels on the total factor productivity (TFP) of Chinese agricultural enterprises and investigate the moderating role of absorptive capacity (technological acumen) on TFP spillover effects.

Based on data from 118 agricultural and related Chinese industries, the authors employ a multithreshold regression model to empirically analyze the impact of FDI on the TFP of agricultural enterprises and the threshold effect of absorptive capacity. To overcome potential endogeneity problems, the authors select the FDI stock of corresponding USA industries and the industrial access policy index as instrumental variables and re-estimate the model.

The results suggest foreign-invested agricultural enterprises are more likely to benefit from FDI, while the “aggregate” FDI spillover effect is negative for domestic agricultural enterprises. However, once threshold effects are introduced, the authors find firms “close to” (“far from”) the technological frontier experience statistically significant positive (negative) spillover effects. Similar results are obtained for virtually all FDI spillover channels for firms in both upstream and downstream industries. FDI spillovers, when they occur, can be a two-edged sword – benefiting some firms at the expense of others.

The authors introduce six FDI spillover channels to examine the impact of FDI on the productivity of foreign-invested and domestic agricultural enterprises. Moreover, the authors analyze the threshold effect of firms' absorptive capacity. These findings can help formulate foreign investment introduction policies based on the characteristics of agricultural enterprises with different ownership structures. These results are also beneficial for agricultural enterprises to better exploit FDI spillover effects and improve their productivity.

A quantitative theoretical model is proposed to measure how productivity performance can be affected by strategic decisions related to specific competitive priorities.

This study proposes the Primary Transformation Model (PTM) and an equation to measure cause-and-effect relationships between productivity and competitive priorities.

The interdependence between productivity and competitive priorities was studied using the PTM and the proposed model indicates that strategies that improve external performance also impact internal productivity. It was also observed that the compatibility between competitive priorities depends on the initial manufacturing conditions and the implementation method adopted.

The proposed model is theoretical and, as such, is an abstraction of reality and does not consider all possible aspects. It consists of a novel approach that still requires further empirical testing. The PTM provides insights about the trade-offs between productivity and strategic objectives, as well, contributes to the ongoing research on manufacturing strategy and can be further developed in future studies.

The main practical implication is to allow companies to relate their strategic decisions to their productivity performance.

This research also contributes to societal issues by enabling firms to better align strategic objectives and operations, which ultimately allows offering products more suited to the needs of customers, thus making better use of the required resources and favoring economic growth.

The model proposed allows objective assessment of actions aiming at operational efficiency and effectiveness, in addition to providing insights into cause-and-effect relationships between productivity and competitive priorities. The model can also be used in empirical investigations on manufacturing strategy.

The paper develops a model for enhancing R&D productivity for Indian public funded laboratories. The paper utilizes the productivity data of five Council of Scientific and Industrial Research (CSIR) laboratories for analysis and to form the constructs of the model.

The weighted average method was employed for analyzing the rankings of survey respondents pertaining to the significant measures enhancing R&D involvement of researchers and significant non-R&D jobs. The authors have proposed a model of productivity. Various individual, organizational and environmental constructs related to the researchers working in the CSIR laboratories have been outlined that can enhance R&D productivity of researchers in Indian R&D laboratories. Partial Least Squares-Structural Equation Modeling (PLS-SEM) was used to find the predictability of the productivity model.

The organizational factors have a crucial role in enhancing the R&D outputs of CSIR laboratories. The R&D productivity of researchers can be improved through implementing the constructs of the proposed model of productivity.

The R&D productivity model can be adapted by the R&D laboratories to enhance researchers’ R&D involvement, increased R&D outputs and achieving self-sustenance in long run.

The R&D laboratories can initiate exercises to explore the most relevant factors and measures to enhance R&D productivity of their researchers. The constructs of the model can function as a guideline to introduce the most preferable research policies in the laboratory for overall mutual growth of laboratory and the researchers.

Hardly any studies have been found that have focused on finding the measures of enhancing R&D involvement of researchers and the influence of significant time-intensive jobs on researchers’ productivity.

This paper explains the mechanisms underlying the generation of two-way knowledge spillovers through the interaction of subsidiaries with differentiated local responsibilities and domestic firms.

The study is based on firm-level panel data from a census of Colombian manufacturing firms for the period 2003–2012. The estimation procedure involves two stages. In the first one, total factor productivity (TFP) of foreign and domestic firms is estimated. In a second step, we estimate conventional spillovers (from foreign-owned to local firms) and reverse spillovers (from local to foreign-owned firms) separately, using a random effect approach.

This study’s findings reveal that only locally creative subsidiaries enjoy positive and significant two-way knowledge spillover effects. The connectivity of subsidiaries to local and international networks is reinforced by reciprocal relationships among actors that enhance bidirectional knowledge flows, these being favored by the dynamics of clustering effects.

The paper contributes with new empirical evidence about the mechanism explaining how the technological heterogeneity of subsidiaries plays a determinant role in the generation of both knowledge flows from foreign to domestic firms and to the reverse, all integrated into the same framework.

Environmental uncertainty (EU) and firm size (FS) generate inertial forces that can push small and medium-sized enterprises (SMEs) to emphasize either exploration or exploitation. In this article, the authors explore how structural (e.g. formal processes, control and discipline) and social (e.g. employee support and decision-making involvement) managerial instruments counteract such inertial forces and enable SME ambidexterity. Building on the organization-context literature, the authors propose a model in which EU and firms' size moderate the relationship between structural and social managerial instruments on SME ambidexterity.

The authors examined a moderation model using surveys of chief executive officers (CEOs) and performance archival data from 237 Chilean SMEs.

The authors find that the positive effect of structure on SME ambidexterity decreases with FS. In contrast, social instruments have a positive effect on ambidexterity for larger firms, especially for those operating in uncertain environments. In cases in which EU and firms' size reinforce the exploration or exploitation tendencies of SMEs, structural and social instruments play a complementary role in achieving ambidexterity.

The authors contribute by proposing a contingent mix of structural and social instruments to enable SME ambidexterity. These results inform policymakers and SME managers by suggesting strategies to promote ambidexterity based on firms' size and EU.

The purpose of this study is to provide new insights into the relationship between fiscal policy and total factor productivity (TFP) while accounting for several economic and econometric issues of the phenomenon like non-stationarity, fiscal feedback effects, persistence in productivity, country heterogeneity and unobserved global shocks and local spillovers affecting heterogeneously the countries in the sample.

The paper is empirical. It builds an Error Correction Model (ECM) specification within a dynamic heterogeneous framework with common correlated effects and models both reverse causality and feedback effects.

The results of this study highlight some new findings relative to the existing related literature. The outcomes suggest some relevant evidence at both the academic and policy levels: (1) the causal effects going from fiscal deficit/surplus to TFP are heterogeneous across countries; (2) the effects depend on the time horizon considered; (3) the long-run dynamics of TFP are positively impacted by improvements in fiscal budget, but only if the austerity measures do not exert slowdowns in aggregate growth.

The main originality of this study is methodological, with possible extensions to related phenomena. Relative to the existing literature, the gains of this study rely on the way econometric techniques, recently proposed in the literature, are adapted to the economic relationship of interest. The endogeneity due to the existence of reverse causality is modelled without implying relevant performance losses of the models. Moreover, this is the first article that questions whether the effects of fiscal budget on productivity depend on the impact of the former on aggregate output growth, thus emphasising the importance of the quality of fiscal adjustments.

Sustainable development involves companies on an individual, organizational and social level requiring the adoption of business models or innovations capable of privileging the co-creation of mutual value with a view to sustainability. From an organizational perspective, this paper aims to show that knowledge brokers, by making explicit their roles as mediators of interactions and acting on dynamic capabilities (DCs), can generate a proactive approach to the three dimensions of sustainability and specifically allows capabilities to positively impact the propensity toward sustainable supply chain management (SSCM) practices.

This study offers an empirical analysis of 200 companies in the agro-food sector participating in a knowledge brokerage system activated by protection consortia. It uses a multiple regression technique that allows for observing relationships between DCs and SSCM.

Absorptive, adaptive and innovative capabilities, when understood and brokered, have a positive and direct impact on the SSCM.

As there have rarely been frameworks developed that correlate knowledge brokerage, DCs and sustainability, this paper suggests that DCs, when adequately valued by the knowledge broker, allow for identifying the requirements of the various stakeholders regarding sustainability and changes in market scenarios to generate sustainability practices along the supply chain.

The present study aimed to assess performance of Industry 4.0 (I4.0) in case organization by considering potential performance measures and analysis using scoring approach.

50 performance measures grouped into five dimensions namely manufacturing management, manufacturing economics, manufacturing strategy, manufacturing technology and workforce were considered for the analysis. The study had been done with relevance to automotive component manufacturing organization. Further, questionnaire for each performance measure was developed to gather expert inputs regarding different performance aspects of I4.0 in case organization. Reliability of the expert responses towards questionnaire was assessed by computing Cronbach's alpha (a) using Statistical Package for the Social Sciences (SPSS) software.

Findings of the study revealed overall I4.0 performance index (OIPI) of 0.71, i.e. 71% signifying improvement scope of 29% pertaining to I4.0 adoption. Gap analysis was performed across dimensions and performance measures to realize the weaker areas. Gap analysis revealed workforce dimension with highest gap and manufacturing management with lowest gap. The gaps that obstruct performance of I4.0 are being recognized and proposals for improvement were provided to the industrial practitioners. Based on further analysis, dimensions and performance measures found to be weaker.

The study helped industrial practitioners and managers to create the foundation for evaluating performance of I4.0-focused organization. Industry practitioners can employ the study to understand different performance measures with respect to different dimensions and realize the significance of I4.0 adoption.

The identification of performance dimensions and measures for I4.0 performance measurement and assessment using scoring approach is the original contribution of the authors.