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Article
Publication date: 29 November 2022

Xiaofang Jia and Xingan Wang

This study intends to explore the relationship between digital finance and the vertical specialization of firms. The following questions are discussed: (1) As a representative new…

Abstract

Purpose

This study intends to explore the relationship between digital finance and the vertical specialization of firms. The following questions are discussed: (1) As a representative new financial development model, what is the role of digital finance in the vertical specialization of firms? (2) If digital finance improves the level of vertical specialization of firms, what is the mechanism behind such improvement? (3) How does digital finance impact the vertical specialization of firms in different regions, industries, and firms?

Design/methodology/approach

A two-way fixed-effect model of panel data is proposed to verify the relationship between digital finance and the vertical specialization of firms. This model is constructed by matching the city-level data of digital finance with the data of China's A-share listed companies from 2011 to 2018. Meanwhile, the instrumental variable (IV) method and difference-in-difference (DID) method are adopted to deal with the endogeneity problem of the model.

Findings

The authors' study finds that digital finance has significantly improved the level of vertical specialization of firms. The result is robust under the endogeneity consideration and a series of robustness tests. After the dimensionality of the index is reduced, the depth of digital finance usage is more conducive to the improvement of the vertical specialization of firms compared with the width of digital finance coverage and the level of financial digitization. Digital finance mainly improves the level of vertical specialization of firms by reducing transaction costs and increasing the market thickness of the intermediate products. Moreover, digital finance has certain heterogeneity in promoting the vertical specialization of firms, an effect that is more significant in the eastern region, manufacturing industry and state-owned enterprises (SOEs).

Research limitations/implications

The first limitation is the mechanism test. This research only analyzes the mechanism from transaction cost and the market thickness of the intermediate products. With the rapid development of information technology, digital finance will be further integrated into people's production and life. There will then be more mechanisms that should be explored between digital finance and the vertical specialization of firms. Another limitation is the data sample of this paper. The conclusions of this research are based only on the data of listed companies. However, in the authors' opinion, the specialization level of small and medium-sized enterprise (SMEs) should be higher. Therefore, the conclusions of this work are underestimated, which can be considered as the lower limit of digital finance for enterprise specialization.

Social implications

As a favorable financing channel to supplement traditional financial service functions, digital finance plays a critical role in the operating efficiency of enterprises and the effective allocation of macro resources. The authors' research shows that digital finance has significantly improved the vertical specialization of firms. This conclusion provides guides to improve the production efficiency of enterprises and the quality of economic development.

Originality/value

This paper has three main contributions. (1) The relationship between financial development and the vertical specialization of firms is innovatively discussed from the perspective of digital finance, which implies that digital finance can effectively promote the level of vertical specialization of firms. (2) This paper provides new perspectives and ideas to reveal the impact mechanism of digital finance on the real economy by systematically analyzing the mechanism of digital finance on the vertical specialization of firms from the perspectives of transaction costs and financing constraints. (3) The regional differences in the development of digital finance, industry differences in the vertical specialization of firms and differences in the nature of enterprise property rights are all under consideration, which improves the effectiveness and pertinence of digital finance in promoting the vertical specialization of firms.

Details

Kybernetes, vol. 53 no. 1
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 22 February 2024

Wenhao Zhou and Hailin Li

This study aims to propose a combined effect framework to explore the relationship between research and development (R&D) team networks, knowledge diversity and breakthrough…

Abstract

Purpose

This study aims to propose a combined effect framework to explore the relationship between research and development (R&D) team networks, knowledge diversity and breakthrough technological innovation. In contrast to conventional linear net effects, the article explores three possible types of team configuration within enterprises and their breakthrough innovation-driving mechanisms based on machine learning methods.

Design/methodology/approach

Based on the patent application data of 2,337 Chinese companies in the biopharmaceutical manufacturing industry to construct the R&D team network, the study uses the K-Means method to explore the configuration types of R&D teams with the principle of greatest intergroup differences. Further, a decision tree model (DT) is utilized to excavate the conditional combined relationships between diverse team network configuration factors, knowledge diversity and breakthrough innovation. The network driving mechanism of corporate breakthrough innovation is analyzed from the perspective of team configurations.

Findings

It has been discerned that in the biopharmaceutical manufacturing industry, there exist three main types of enterprise R&D team configurations: tight collaboration, knowledge expansion and scale orientation, which reflect the three resource investment preferences of enterprises in technological innovation, network relationships, knowledge resources and human capital. The results highlight both the crowding-out effects and complementary effects between knowledge diversity and team network characteristics in tight collaborative teams. Low knowledge diversity and high team structure holes (SHs) are found to be the optimal team configuration conditions for breakthrough innovation in knowledge-expanding and scale-oriented teams.

Originality/value

Previous studies have mainly focused on the relationship between the external collaboration network and corporate innovation. Moreover, traditional regression methods mainly describe the linear net effects between variables, neglecting that technological breakthroughs are a comprehensive concept that requires the combined action of multiple factors. To address the gap, this article proposes a combination effect framework between R&D teams and enterprise breakthrough innovation, further improving social network theory and expanding the applicability of data mining methods in the field of innovation management.

Details

European Journal of Innovation Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1460-1060

Keywords

Article
Publication date: 10 January 2024

He-Boong Kwon, Jooh Lee and Ian Brennan

This study aims to explore the dynamic interplay of key resources (i.e. research and development (R&D), advertising and exports) in affecting the performance of USA manufacturing…

Abstract

Purpose

This study aims to explore the dynamic interplay of key resources (i.e. research and development (R&D), advertising and exports) in affecting the performance of USA manufacturing firms. Specifically, the authors examine the dynamic impact of joint resources and predict differential effect scales contingent on firm capabilities.

Design/methodology/approach

This study presents a combined multiple regression analysis (MRA)-multilayer perceptron (MLP) neural network modeling and investigates the complex interlinkage of capabilities, resources and performance. As an innovative approach, the MRA-MLP model investigates the effect of capabilities under the combinatory deployment of joint resources.

Findings

This study finds that the impact of joint resources and synergistic rents is not uniform but rather distinctive according to the combinatory conditions and that the pattern is further shaped by firm capabilities. Accordingly, besides signifying the contingent aspect of capabilities across a range of resource combinations, the result also shows that managerial sophistication in adaptive resource control is more than a managerial ethos.

Practical implications

The proposed analytic process provides scientific decision support tools with control mechanisms with respect to deploying multiple resources and setting actionable goals, thereby presenting pragmatic benchmarking options to industry managers.

Originality/value

Using the theoretical underpinnings of the resource-based view (RBV) and resource orchestration, this study advances knowledge about the complex interaction of key resources by presenting a salient analytic process. The empirical design, which portrays holistic interaction patterns, adds to the uniqueness of this study of the complex interlinkages between capabilities, resources and shareholder value.

Details

Benchmarking: An International Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1463-5771

Keywords

Article
Publication date: 21 June 2023

Dwi Ratna Hidayati, Elena Garnevska and Thiagarajah Ramilan

Agrifood value chains in developing countries are transforming into higher value markets which require sustainable practices, with smallholders playing a critical role. However…

Abstract

Purpose

Agrifood value chains in developing countries are transforming into higher value markets which require sustainable practices, with smallholders playing a critical role. However, smallholders are a heterogeneous group which may have discrepancies in outcomes to meet sustainability standards. This paper aims to empirically investigate smallholders' heterogeneity towards sustainable value chain practice in developing countries.

Design/methodology/approach

Eight key enabling factors of sustainable value chain transformation were used to explore smallholders' typology, then profiled, based on their socio-economic status and current practices. A quantitative method was applied in Indonesia's cashew sector with 159 respondents from the primary producer area on Madura Island. A combination of descriptive analysis, cluster analysis, cross-tab analysis and one-way ANOVA analysis was used in this study.

Findings

Four types of groups were identified, each with distinct characteristics and arranged in priority order as follows: accelerator, progressor, inattentive and conservative groups. Interventions can be implemented on per clusters basis or based on potential similarities among clusters, depending on priority. It is noted that the pursuit of sustainable value chain practices by smallholders is not necessarily associated with high socio-economic status, as those with low socio-economic status may have a stronger inclination towards them.

Practical implications

The paper enhances awareness of practitioners and policymakers regarding smallholders' heterogeneity in sustainable value chain practice. It enables more effective and focused interventions to support smallholders who require assistance in sustainable production and value-adding activities. Different smallholders' characteristics call for different assistance/intervention. Practitioners can recognise smallholders' characteristics that are more compatible with higher value markets and sustainability requirements to better integrate their practices. Policymakers must carefully develop short-term and long-term interventions based on the activities prioritised by particular traits to “hit the right button” for smallholders' practice development.

Originality/value

This study investigates the typology of smallholders towards sustainable value chain practices by using eight enabling factors and profiling them based on their socio-economic condition and current practices. Additionally, this study shifts the focus of typology exploration away from the traditional lens of farm sustainability to a larger perspective which encompasses sustainable value chain activities.

Details

British Food Journal, vol. 125 no. 12
Type: Research Article
ISSN: 0007-070X

Keywords

Article
Publication date: 6 July 2023

Biasino Farace and Angela Tarabella

This research aims to investigate the role of digitalization in facilitating the integration of circular economy (CE) principles within a firm operating in the Italian agrifood…

Abstract

Purpose

This research aims to investigate the role of digitalization in facilitating the integration of circular economy (CE) principles within a firm operating in the Italian agrifood sector. The study seeks to explore the evidence and effects emerging from the adoption of digital technologies in a small and medium enterprise (SME) operational setting.

Design/methodology/approach

An interpretative case study was conducted on an SME operating in the Italian agrifood sector. The selected firm is known to adopt a business model oriented towards circularity by using entirely digitized closed-loop hydroponic cultivation.

Findings

The findings reveal that the digitalization of the production process, supported by an integrated information system, enables optimizing the use and consumption of natural resources and minimizes waste during the production stage. Additionally, the authors observed that digitalization triggers a complex mechanism of interaction between various firm factors, market dynamics and forms of institutionalization, which are intrinsically intertwined with the concepts of sustainability and resilience in the agrifood sector.

Originality/value

From a theoretical point of view, the interpretive reading key – historically appropriate to embrace the complexity of the phenomena under study – can foster a deeper understanding of the dynamics underlying digitalization as an enabling factor to facilitating the adoption of CE principles in the agrifood sector. Regarding managerial implications, the study contributes to the debate on the importance of digital transition in the agrifood industry, which in the Italian context shows considerable resistance due, especially, to the size of the firms (mainly SMEs and micro) and managerial conservatism tradition.

Details

British Food Journal, vol. 126 no. 1
Type: Research Article
ISSN: 0007-070X

Keywords

Book part
Publication date: 18 January 2024

Mahendra Gooroochurn and Riaan Stopforth

Industry 4.0 has been identified as a key cornerstone to modernise economies where man and machines complement each other seamlessly to achieve synergies in decision-making and…

Abstract

Industry 4.0 has been identified as a key cornerstone to modernise economies where man and machines complement each other seamlessly to achieve synergies in decision-making and productivity for contributing to SDG 8: Decent Work and Economic Growth and SDG 9: Industry, Innovation and Infrastructure. The integration of Industry 4.0 remains a challenge for the developing world, depending on their current status in the industrial revolution journey from its predecessors 1.0, 2.0 and 3.0. This chapter reviews reported findings in literature to highlight how robotics and automated systems can pave the way to implementing and applying the principles of Industry 4.0 for developing countries like Mauritius, where data collection, processing and analysis for decision-making and prediction are key components to be integrated or designed into industrial processes centred heavily on the use of artificial intelligence (AI) and machine learning techniques. Robotics has not yet found its way into the various industrial sectors in Mauritius, although it has been an important driver for Industry 4.0 across the world. The inherent barriers and transformations needed as well as the potential application scenarios are discussed.

Details

Artificial Intelligence, Engineering Systems and Sustainable Development
Type: Book
ISBN: 978-1-83753-540-8

Keywords

Article
Publication date: 22 December 2023

Jungmi Oh

Climate change-induced weather changes are severe and frequent, making it difficult to predict apparel sales. The primary goal of this study was to assess consumers' responses to…

Abstract

Purpose

Climate change-induced weather changes are severe and frequent, making it difficult to predict apparel sales. The primary goal of this study was to assess consumers' responses to winter apparel searches when external stimuli, such as weather, calendars and promotions arise and to develop a decision-making tool that allows apparel retailers to establish sales strategies according to external stimuli.

Design/methodology/approach

The theoretical framework of this study was the effect of external stimuli, such as calendar, promotion and weather, on seasonal apparel search in a consumer's decision-making process. Using weather observation data and Google Trends over the past 12 years, from 2008 to 2020, consumers' responses to external stimuli were analyzed using a classification and regression tree to gain consumer insights into the decision process. The relative importance of the factors in the model was determined, a tree model was developed and the model was tested.

Findings

Winter apparel searches increased when the average, maximum and minimum temperatures, windchill, and the previous day's windchill decreased. The month of the year varies depending on weather factors, and promotional sales events do not increase search activities for seasonal apparel. However, sales events during the higher-than-normal temperature season triggered search activity for seasonal apparel.

Originality/value

Consumer responses to external stimuli were analyzed through classification and regression trees to discover consumer insights into the decision-making process to improve stock management because climate change-induced weather changes are unpredictable.

Details

Journal of Fashion Marketing and Management: An International Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1361-2026

Keywords

Article
Publication date: 29 September 2023

Niki Kyriakou, Euripidis N. Loukis and Manolis Maragoudakis

This study aims to develop a methodology for predicting the resilience of individual firms to economic crisis, using historical government data to optimize one of the most…

Abstract

Purpose

This study aims to develop a methodology for predicting the resilience of individual firms to economic crisis, using historical government data to optimize one of the most important and costly interventions that governments undertake, the huge economic stimulus programs that governments implement for mitigating the consequences of economic crises, by making them more focused on the less resilient and more vulnerable firms to the crisis, which have the highest need for government assistance and support.

Design/methodology/approach

The authors are leveraging existing firm-level data for economic crisis periods from government agencies having competencies/responsibilities in the domain of economy, such as Ministries of Finance and Statistical Authorities, to construct prediction models of the resilience of individual firms to the economic crisis based on firms’ characteristics (such as human resources, technology, strategies, processes and structure), using artificial intelligence (AI) techniques from the area of machine learning (ML).

Findings

The methodology has been applied using data from the Greek Ministry of Finance and Statistical Authority about 363 firms for the Greek economic crisis period 2009–2014 and has provided a satisfactory prediction of a measure of the resilience of individual firms to an economic crisis.

Research limitations/implications

The authors’ study opens up new research directions concerning the exploitation of AI/ML in government for a critical government activity/intervention of high importance that mobilizes/spends huge financial resources. The main limitation is that the abovementioned first application of the proposed methodology has been based on a rather small data set from a single national context (Greece), so it is necessary to proceed to further application of this methodology using larger data sets and different national contexts.

Practical implications

The proposed methodology enables government agencies responsible for the implementation of such economic stimulus programs to proceed to radical transformations of them by predicting the resilience to economic crisis of the firms applying for government assistance and then directing/focusing the scarce available financial resources to/on the ones predicted to be more vulnerable, increasing substantially the effectiveness of these programs and the economic/social value they generate.

Originality/value

To the best of the authors’ knowledge, this study is the first application of AI/ML in government that leverages existing data for economic crisis periods to optimize and increase the effectiveness of the largest and most important and costly economic intervention that governments repeatedly have to make: the economic stimulus programs for mitigating the consequences of economic crises.

Details

Transforming Government: People, Process and Policy, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1750-6166

Keywords

Article
Publication date: 8 May 2023

Megita Ryanjani Tanuputri and Hu Bai

Determining vulnerability and resilience is necessary to develop sustainable agribusiness. The purpose of this study is to clarify and understand the current condition and…

Abstract

Purpose

Determining vulnerability and resilience is necessary to develop sustainable agribusiness. The purpose of this study is to clarify and understand the current condition and problems in the tea supply chain and to develop a framework on how to build a sustainable and resilient tea supply chain.

Design/methodology/approach

This study is a case study analysis which develops an integrated framework to build a resilient tea supply chain. It evaluates and extends the current knowledge of Javanese tea by applying business process analysis to understand the situation.

Findings

This paper develops an integrated and conceptual framework on how to build resilient supply chain by considering five broad factors: vulnerability analysis, assessment of assets, supply chain collaboration, control mechanism from government and outcome.

Research limitations/implications

The framework provides a conceptual view but limited to field surveys in Central Java Province. This study could increase the general understanding of tea supply chain in Indonesia and its major problems and challenges.

Practical implications

The framework also highlights different stakeholder's organizational constraints and issues, especially during the COVID-19 pandemic.

Originality/value

The business process analysis and conceptual framework offer an expanded and in-depth explanation on how organizations respond to the changing conditions, especially during the COVID-19 pandemic.

Details

The International Journal of Logistics Management, vol. 34 no. 6
Type: Research Article
ISSN: 0957-4093

Keywords

Article
Publication date: 27 February 2023

Guanxiong Wang, Xiaojian Hu and Ting Wang

By introducing the mass customization service mode into the cloud logistics environment, this paper studies the joint optimization of service provider selection and customer order…

192

Abstract

Purpose

By introducing the mass customization service mode into the cloud logistics environment, this paper studies the joint optimization of service provider selection and customer order decoupling point (CODP) positioning based on the mass customization service mode to provide customers with more diversified and personalized service content with lower total logistics service cost.

Design/methodology/approach

This paper addresses the general process of service composition optimization based on the mass customization mode in a cloud logistics service environment and constructs a joint decision model for service provider selection and CODP positioning. In the model, the two objective functions of minimum service cost and most satisfactory delivery time are considered, and the Pareto optimal solution of the model is obtained via the NSGA-II algorithm. Then, a numerical case is used to verify the superiority of the service composition scheme based on the mass customization mode over the general scheme and to verify the significant impact of the scale effect coefficient on the optimal CODP location.

Findings

(1) Under the cloud logistics mode, the implementation of the logistics service mode based on mass customization can not only reduce the total cost of logistics services by means of the scale effect of massive orders on the cloud platform but also make more efficient use of a large number of logistics service providers gathered on the cloud platform to provide customers with more customized and diversified service content. (2) The scale effect coefficient directly affects the total cost of logistics services and significantly affects the location of the CODP. Therefore, before implementing the mass customization logistics service mode, the most reasonable clustering of orders on the cloud logistics platform is very important for the follow-up service combination.

Originality/value

The originality of this paper includes two aspects. One is to introduce the mass customization mode in the cloud logistics service environment for the first time and summarize the operation process of implementing the mass customization mode in the cloud logistics environment. Second, in order to solve the joint decision optimization model of provider selection and CODP positioning, this paper designs a method for solving a mixed-integer nonlinear programming model using a multi-layer coding genetic algorithm.

Details

Kybernetes, vol. 53 no. 4
Type: Research Article
ISSN: 0368-492X

Keywords

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