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Book part
Publication date: 3 February 2025

Chandrima Chakraborty and Dipyaman Pal

Abstract

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Performance Analysis of the Indian Pharmaceutical Industry: A Global Outlook
Type: Book
ISBN: 978-1-83797-743-7

Available. Open Access. Open Access
Article
Publication date: 28 November 2023

Timothy Manyise, Domenico Dentoni and Jacques Trienekens

This paper aims to investigate the entrepreneurial behaviours exhibited by commercial smallholder farmers in Zimbabwe, focusing on their socio-economic characteristics, and…

1336

Abstract

Purpose

This paper aims to investigate the entrepreneurial behaviours exhibited by commercial smallholder farmers in Zimbabwe, focusing on their socio-economic characteristics, and considers their implication for outcomes of livelihood resilience in a resource-constrained and turbulent rural context.

Design/methodology/approach

The study used survey data collected from 430 smallholder farmers in Masvingo province, Zimbabwe. Using a two-step cluster analysis, the study constructed a typology of farmers based on their entrepreneurial behaviour and socio-economic characteristics.

Findings

The results revealed that commercial smallholder farmers are heterogeneous in terms of their entrepreneurial behaviours. Four clusters were identified: non-entrepreneurial, goal-driven, means-driven and ambidextrous. Beyond their entrepreneurial behaviours, these clusters significantly differ in the socio-economic characterises (gender, age, education levels, farm size, proximity to the market and social connection) and farm performance (seasonal sales per hectare and farm income per hectare).

Research limitations/implications

The typology framework relating farmers’ entrepreneurial behaviours to their socio-economic characteristics and business performance is important to tailor and therefore improve the effectiveness of farmer entrepreneurship programmes and policies. In particular, tailoring farmer entrepreneurship education is crucial to distribute land, finance and market resources in purposive ways to promote a combination of smallholder farmers’ effectual and causal behaviours at an early stage of their farm ventures.

Originality/value

Researchers still know little about which farmers’ behaviours are entrepreneurial and how these behaviours manifest in action during their commercial farm activities. This research leverages effectuation and causation theory to unveil previously overlooked distinctions on farmers’ entrepreneurial behaviours, thereby enhancing a more grounded understanding of farmer entrepreneurship in a resource-constrained context.

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Journal of Entrepreneurship in Emerging Economies, vol. 17 no. 7
Type: Research Article
ISSN: 2053-4604

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Article
Publication date: 3 June 2024

Shenglong Chen, Jiannan Cai, Karina Bogatyreva and Ewuradjoa Quansah

Small- and medium-sized enterprises (SMEs) increasingly implement digitalization in uncertain business environments. However, a dearth exists in the entrepreneurship literature…

302

Abstract

Purpose

Small- and medium-sized enterprises (SMEs) increasingly implement digitalization in uncertain business environments. However, a dearth exists in the entrepreneurship literature for understanding the decision-making logic of digitalization as a management issue. Drawing on the effectuation theory, this study aims to explore the relationships between effectuation dimensions and SMEs’ digitalization.

Design/methodology/approach

Using quantitative data collected from 345 Chinese SMEs through questionnaires, the authors conducted the principal component analysis and hierarchical linear regression analysis.

Findings

The results highlight significant positive relationships between the four effectuation elements – experimentation, affordable loss, flexibility and precommitment – and SMEs’ digitalization. Moreover, this research considers the environmental conditions as moderators and reveals that environmental dynamism and complexity associated with high uncertainty negatively moderate the effects of effectuation on SMEs’ digitalization.

Practical implications

SMEs embarking on digitalization should constantly experiment to determine optimal strategies while contemplating their affordable losses. Flexibility should also be maintained to discard unproductive tactics and redirect to other viable options. Additionally, precommitments can reduce the risk that SMEs encounter in digitalization process. While the effectuation principles consolidate the likelihood of a successful digitalization, this research recommends that entrepreneurs should carefully consider their possible application in uncertain environments.

Originality/value

This study contributes to the entrepreneurship literature by theoretically clarifying the decision-making mechanism of digitalization and extends the application of effectuation to this context by illuminating the influences of effectuation principles on SMEs’ digital transformation. The identification of negative moderating effects of environmental uncertainty also augments an academic criticism about uncertainty creating the conditions for effectuation.

Details

Journal of Entrepreneurship in Emerging Economies, vol. 17 no. 2
Type: Research Article
ISSN: 2053-4604

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Article
Publication date: 20 February 2023

Peiyu Ou and Chenxi Zhang

Although the financial shared service (FSS) mode has become a well-established organizational arrangement, current information system (IS) research remains limited and mixed. The…

528

Abstract

Purpose

Although the financial shared service (FSS) mode has become a well-established organizational arrangement, current information system (IS) research remains limited and mixed. The purpose of this study is to narrow research gaps in the literature on shared services from an FSS practice perspective. The following research questions guide this study: (1) what are the important antecedents of FSS implementation? (2) what is the impact of FSS implementation on firm performance?

Design/methodology/approach

Drawing on the technology–organization–environment (TOE) framework and previous innovation studies, this study explores the impact of FSS implementation on firm performance. A questionnaire survey was conducted on Chinese firms using partial least squares (PLS) for data analysis.

Findings

The authors find technological, organizational and environmental factors affect the extent and depth of FSS implementation. The empirical results show that relative advantage, compatibility, top management support, managerial obstacles and competitive pressure significantly affect FSS implementation, but bandwagon pressure does not have a direct impact on it. Top management support is the most important factor, and managerial obstacles and compatibility are controllable and manageable factors for firms. The study confirms that FSS improves the financial and non-financial performance of firms significantly, and the degree of improvement in non-financial is greater than that in financial performance.

Practical implications

A comprehension of the key factors influencing FSS implementation will help companies predict weaknesses in their implementation plan and design suitable strategies to handle deployment to achieve these benefits. Managers can make a comprehensive decision regarding the long-term development of combining FSS and the suitability of companies.

Originality/value

The findings contribute to the shared services implementation theory by identifying a set of theoretical factors that shape a firm's shared service implementation. This study provides empirical support to gauge the impact of FSS implementation on firm performance and provides new evidence for a shared-service payoff study. Moreover, the study extends the applicability of the TOE framework and the balanced scorecard (BSC) viewpoint to the FSS implementation field.

Details

Journal of Enterprise Information Management, vol. 38 no. 1
Type: Research Article
ISSN: 1741-0398

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Article
Publication date: 17 May 2024

Shan Wang and Fang Wang

In social marketplaces, follower ego networks are integral social capital assets for online sellers. While previous research has underscored the positive impact of the follower…

98

Abstract

Purpose

In social marketplaces, follower ego networks are integral social capital assets for online sellers. While previous research has underscored the positive impact of the follower number on seller performance, little attention has been given to the structure of follower networks and their value implications. This research investigates two structural properties of follower networks—network centralization and density—and examines their main and contingent effects on sellers’ sales performance.

Design/methodology/approach

A 13-month panel dataset of 1,150 sellers in Etsy, a social marketplace for handmade and vintage products, was collected and analyzed. A fixed effects model was adopted to validate the hypotheses on the main effect of centralization and density, as well as the moderating effects of two store attributes: store age and product diversification.

Findings

We find that both network centralization and density negatively impact sellers’ sales performance, and these effects vary across store age and product diversification levels. Specifically, the negative effect of network centralization is less pronounced for older stores than young ones, whereas the negative effect of density is more severe for stores with high product diversification.

Originality/value

This research contributes to social commerce research by highlighting the significance of network structure, alongside network size, in assessing the value of followers and offers practical guidance for sellers in social marketplaces seeking to optimize their follower networks.

Details

Internet Research, vol. 35 no. 1
Type: Research Article
ISSN: 1066-2243

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Article
Publication date: 12 November 2024

Gentrit Berisha, Rrezon Lajçi, Andreas Kallmuenzer and Besnik Krasniqi

This study aims to investigate the drivers of the internationalization scope of born global from the digital and software solution sector in an emerging economy context, which…

50

Abstract

Purpose

This study aims to investigate the drivers of the internationalization scope of born global from the digital and software solution sector in an emerging economy context, which presents an unexplored avenue of research. This study endeavors to understand the individual and market-level drivers of internationalization scope. Relying on the effectuation and causation framework and reactive/proactive driver typology, this paper sheds light on the individual decision-maker’s makeup and market conditions that influence the changes between strategies in the internationalization process.

Design/methodology/approach

A qualitative multiple case study approach is used to explore drivers of the internationalization scope of born globals. Seven born globals from the digital and software solution sectors were depicted, and interviews with their founders were conducted.

Findings

Study findings support the utilization of effectuation theory in explaining the scope of internationalization of born globals. Furthermore, the findings attest that the two decision-making logics are interchangeable. On the market level, several context-specific factors have stirred the diversity of markets pursued by born globals. The findings evince that the founders of the born globals perceive the domestic market as small and underdeveloped; therefore, they seek more developed, easily accessible, distant markets.

Originality/value

The study contributes to a better understanding of the internationalization of born globals in an emerging economy context. We find that born globals change their strategies iteratively with the stage of internationalization.

Details

Journal of Organizational Change Management, vol. 38 no. 1
Type: Research Article
ISSN: 0953-4814

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Article
Publication date: 26 November 2024

Aneel Manan, Zhang Pu, Jawad Ahmad and Muhammad Umar

Rapid industrialization and construction generate substantial concrete waste, leading to significant environmental issues. Nearly 10 billion metric tonnes of concrete waste are…

31

Abstract

Purpose

Rapid industrialization and construction generate substantial concrete waste, leading to significant environmental issues. Nearly 10 billion metric tonnes of concrete waste are produced globally per year. In addition, concrete also accelerates the consumption of natural resources, leading to the depletion of these natural resources. Therefore, this study uses artificial intelligence (AI) to examine the utilization of recycled concrete aggregate (RCA) in concrete.

Design/methodology/approach

An extensive database of 583 data points are collected from the literature for predictive modeling. Four machine learning algorithms, namely artificial neural network (ANN), random forest (RF), ridge regression (RR) and least adjacent shrinkage and selection operator (LASSO) regression (LR), in predicting simultaneously concrete compressive and tensile strength were evaluated. The dataset contains 10 independent variables and two dependent variables. Statistical parameters, including coefficient of determination (R2), mean square error (MSE), mean absolute error (MAE) and root mean square error (RMSE), were employed to assess the accuracy of the algorithms. In addition, K-fold cross-validation was employed to validate the obtained results, and SHapley Additive exPlanations (SHAP) analysis was applied to identify the most sensitive parameters out of the 10 input parameters.

Findings

The results indicate that the RF prediction model performance is better and more satisfactory than other algorithms. Furthermore, the ANN algorithm ranks as the second most accurate algorithm. However, RR and LR exhibit poor findings with low accuracy. K-fold cross-validation was successfully applied to validate the obtained results and SHAP analysis indicates that cement content and recycled aggregate percentages are the effective input parameter. Therefore, special attention should be given to sensitive parameters to enhance the concrete performance.

Originality/value

This study uniquely applies AI to optimize the use of RCA in concrete production. By evaluating four machine learning algorithms, ANN, RF, RR and LR on a comprehensive dataset, this study identities the most effective predictive models for concrete compressive and tensile strength. The use of SHAP analysis to determine key input parameters and K-fold cross-validation for result validation adds to the study robustness. The findings highlight the superior performance of the RF model and provide actionable insights into enhancing concrete performance with RCA, contributing to sustainable construction practice.

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Article
Publication date: 5 September 2023

Zhenghao Tong, Soyeong Lee and Hongjoo Woo

This study aims to examine the effects of perceived product–brand fit and brand type on consumer evaluations of wearable smart masks’ technological, aesthetic and social…

219

Abstract

Purpose

This study aims to examine the effects of perceived product–brand fit and brand type on consumer evaluations of wearable smart masks’ technological, aesthetic and social attributes and how these affect consumers’ attitudes and intentions to use.

Design/methodology/approach

Through an experimental approach, a total of 240 US consumers’ evaluations of smart masks are compared according to perceived product–brand fit (high vs low) and brand type (electronics vs fashion).

Findings

The results showed that high perceived product–brand fit increases consumers’ evaluations, while brand type did not significantly affect consumers’ evaluations. Among various attributes, social acceptability had the greatest influence on consumers’ attitude and intention to use. Perceived ease of use, however, positively influenced attitude but negatively influenced intention to use.

Originality/value

As consumers’ interest in smart health-care wearables increases and air pollution is a serious issue across countries, research on wearable smart masks is being facilitated. Smart masks refer to the digitalized, reusable wearable masks that provide protection and health-care functions. However, their market penetration is still limited. To close this gap between smart mask technology and the market, this study examines how perceived fit and brand type can be used to enhance consumer evaluations.

Details

Research Journal of Textile and Apparel, vol. 29 no. 1
Type: Research Article
ISSN: 1560-6074

Keywords

Available. Open Access. Open Access
Article
Publication date: 10 October 2024

Xu Cao and Lei Wang

This study aims to explore the traditional plant dyeing of Xinjiang Atlas silk fabrics, providing references for the comprehensive utilization of plant dyes in intangible…

152

Abstract

Purpose

This study aims to explore the traditional plant dyeing of Xinjiang Atlas silk fabrics, providing references for the comprehensive utilization of plant dyes in intangible cultural heritage.

Design/methodology/approach

The focus of this study is on dyeing experiments of Atlas silk fabrics using safflower extracts, constrained by regional resources. Safflower dry flowers grown in Xinjiang were selected, rinsed with pure water and rubbed. Yellow pigments were removed by adding edible white vinegar. Red pigments from safflower were extracted using an alkaline solution prepared with Populus euphratica ash, a special product of Xinjiang. The extraction rate was analyzed under varying material-to-liquor ratios, pH values, times and temperatures. Direct dyeing process experiments were conducted to obtain different colorimetric L, a, b and K/S values for comparison. Samples with good color development were selected to test the impact of dyeing immersions on color development, and their color fastness, UV protection and antibacterial effects were verified.

Findings

The dyeing experiments on silk fabrics confirmed their UV protection capabilities and antibacterial properties, demonstrating effectiveness against E. coli and Staphylococcus aureus. As a major producer of safflower, Xinjiang underscores the significance of safflower as an essential plant dyes on the Silk Road. This study reveals its market potential and suitability for use in the plant dyeing process of Atlas silk, producing vibrant red and pink colors.

Originality/value

The experiments indicated that after removing yellow pigments, the highest extraction rate of red pigment from safflower was achieved at a pH value of 10–11, a temperature of 30°C and an extraction time of 40 min. The best bright red color effect with strong color fastness was obtained with a material-to-liquor ratio of 1:20, a temperature of 40°C and three immersions. The best light pink color effect with strong color fastness was a material-to-liquor ratio of 1:80, a temperature of 30°C and two immersions.

Details

International Journal of Clothing Science and Technology, vol. 37 no. 1
Type: Research Article
ISSN: 0955-6222

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Article
Publication date: 20 January 2025

Cong Doanh Duong, Thanh Hieu Nguyen, Thi Viet Nga Ngo, Thu Van Bui and Nhat Minh Tran

The current study aims to investigate the impact of perceived blockchain-related information transparency on consumers’ intention to purchase organic food. This study examines how…

62

Abstract

Purpose

The current study aims to investigate the impact of perceived blockchain-related information transparency on consumers’ intention to purchase organic food. This study examines how perceived blockchain- related information transparency, directly and indirectly, affects purchase intentions through attitudes, perceived behavioural control and subjective norms. Additionally, the study explores how blockchain-based trust moderates the influence of perceived blockchain-related information transparency on these factors and the intention to purchase organic food.

Design/methodology/approach

Based on the theory of planned behaviour framework and a sample of 5,326 consumers, this study uses partial least squares structural equation modelling to test the research model.

Findings

This study finds that perceived blockchain-related information transparency directly enhances consumers’ attitudes towards organic food purchase, perceived behavioural control, subjective norms and intention to purchase organic food. Additionally, perceived blockchain-related information transparency indirectly affects consumers’ intention to buy organic food through three antecedents of the theory of planned behaviour model. Notably, these indirect effects were moderated by consumers’ blockchain-based trust.

Practical implications

This study provides recommendations for leveraging blockchain to enhance transparency and build trust, which could boost consumer engagement and organic food purchases.

Originality/value

This research contributes to blockchain literature by empirically examining the role of perceived blockchain-related transparency and blockchain-based trust in consumers’ purchasing decisions regarding organic food. It provides valuable insights into the consumer-centric benefits of blockchain technology. Furthermore, this study also contributes to the literature on organic food, particularly its promotion through blockchain technology.

Details

British Food Journal, vol. 127 no. 3
Type: Research Article
ISSN: 0007-070X

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