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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…
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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Xiang Yu, Yuichi Washida and Masato Sasaki
This study aims to examine direct effects of qualified team gatekeepers on absorptive capacity (AC), and the mediating roles of combinative capabilities – knowledge integration…
Abstract
Purpose
This study aims to examine direct effects of qualified team gatekeepers on absorptive capacity (AC), and the mediating roles of combinative capabilities – knowledge integration capability (KIC) and interteam coordination.
Design/methodology/approach
A social networking analysis was used to analyze a unique data set collected from all members of 32 Japanese research and development (R&D) teams to identify key individuals who perform daily gatekeeping functions. This study analyzed the data through partial least squares structural equation modeling with higher-order latent variables. Finally, cross-validation tests were used with holdout samples to test the model’s predictive validity.
Findings
Qualified gatekeepers directly contribute to teams’ realized AC but not to their potential AC. Furthermore, qualified gatekeepers can improve their teams’ capability to absorb and exploit external knowledge by facilitating their capability to consolidate knowledge, that is, its KIC and interteam coordination.
Originality/value
Unlike prior research that asks top managers to identify team gatekeepers, this study used social network analysis to identify these vital individuals. This study provides a new framework indicating how qualified gatekeepers impact the AC of R&D teams through the examination of both the direct and indirect paths of gatekeeping abilities, two combinative capabilities as mediators and team AC.
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Owais Khan and Andreas Hinterhuber
The role of procurement managers is crucial for diffusing sustainability throughout the supply chain. Whether or not they are willing to pay for sustainability is an important and…
Abstract
Purpose
The role of procurement managers is crucial for diffusing sustainability throughout the supply chain. Whether or not they are willing to pay for sustainability is an important and not yet fully understood question. The authors examine antecedents and consequences of their willingness to pay (WTP) for sustainability.
Design/methodology/approach
The authors develop a multi-level framework to examine the WTP for sustainability in a B2B context. The authors test this multi-level framework with 372 procurement managers from multiple sectors and countries using partial least squares structural equation modeling.
Findings
The authors find that individual values of procurement managers and institutional pressures directly, while ethical organizational culture indirectly influence WTP for sustainability. Functional and cognitive competencies of procurement managers improve the sustainability of procurement, but not WTP for sustainability. Importantly, WTP for sustainability directly influences the performance of the procurement function which in turn is positively associated with increased organizational performance.
Originality/value
The study, examining the interplay between individual, organizational and contextual factors, provides empirical evidence on the pivotal role of procurement managers in diffusing sustainability throughout the supply chain. The findings of the study, on the one hand, contribute to the literature on operations management and sustainability, and on the other hand, guide policy and managerial actions.
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Lucia Pizzichini, Valerio Temperini, Federica Caboni and Armando Papa
This paper aims to contribute to overcoming the gap existing in the supply chain literature related to digital servitization by bridging digital servitization with knowledge…
Abstract
Purpose
This paper aims to contribute to overcoming the gap existing in the supply chain literature related to digital servitization by bridging digital servitization with knowledge management and identifying the rise of digital knowledge servitization as a driver for changes in the supply chain business model towards open innovation.
Design/methodology/approach
The study follows an inductive grounded theory approach for theory building. To analyse the impact of digital knowledge servitization, in-depth interviews of managers in the main business units of the Volvo Group supply chain ecosystem were carried out.
Findings
The results show how the digital servitization process affects the supply chain business model, highlighting the central role of knowledge in the service ecosystem and the rise of the theoretical concept of digital knowledge servitization. In particular, through the Innovation Lab (Volvo Group) study, the paper contributes to bringing together the theoretical knowledge-based view of servitization with the digital servitization concept, which demonstrates the role of this combined perspective in the transformation of the supply chain; this is carried out by introducing a new business model based on open innovation in inbound and outbound processes.
Practical implications
The research offers interesting insights from a managerial perspective, as increasingly advanced and complex digital solutions require shorter times in supply chain management (SCM). Companies need to be able to quickly manage information and knowledge flows deriving from internal and external interactions and involvement with external actors upstream and downstream of the supply chain ecosystem. Therefore, the digital knowledge servitization of the supply chain also highlights implications for managers in terms of human resources management.
Originality/value
The novel research goal is to contribute to the supply chain literature by integrating the digital servitization with the knowledge view and analysing the impact on the inbound and outbound supply chain through the introduction of an open innovation business model.
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Mohammad Islam Biswas, Md. Shamim Talukder and Atikur Rahman Khan
Firms have already begun integrating artificial intelligence (AI) as a replacement for conventional performance management systems owing to its technological superiority. This…
Abstract
Purpose
Firms have already begun integrating artificial intelligence (AI) as a replacement for conventional performance management systems owing to its technological superiority. This transition has sparked a growing interest in determining how employees perceive and respond to performance feedback provided by AI as opposed to human supervisors.
Design/methodology/approach
A 2 x 2 between-subject experimental design was employed that was manipulated into four experimental conditions: AI algorithms, AI data, highly experienced human supervisors and low-experience human supervisor conditions. A one-way ANOVA and Welch t-test were used to analyze data.
Findings
Our findings revealed that with a predefined fixed formula employed for performance feedback, employees exhibited higher levels of trust in AI algorithms, had greater performance expectations and showed stronger intentions to seek performance feedback from AI algorithms than highly experienced human supervisors. Conversely, when performance feedback was provided by human supervisors, even those with less experience, in a discretionary manner, employees' perceptions were higher compared to similar feedback provided by AI data. Moreover, additional analysis findings indicated that combined AI-human performance feedback led to higher levels of employees' perceptions compared to performance feedback solely by AI or humans.
Practical implications
The findings of our study advocate the incorporation of AI in performance management systems and the implementation of AI-human combined feedback approaches as a potential strategy to alleviate the negative perception of employees, thereby increasing firms' return on AI investment.
Originality/value
Our study represents one of the initial endeavors exploring the integration of AI in performance management systems and AI-human collaboration in providing performance feedback to employees.
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Giampiero Donnici, Marco Freddi and Alfredo Liverani
In this study, response surface methodology (RSM) is applied to a three-point bending stiffness analysis of low-cost material (PLA) specimens printed using FDM technology to…
Abstract
Purpose
In this study, response surface methodology (RSM) is applied to a three-point bending stiffness analysis of low-cost material (PLA) specimens printed using FDM technology to analyze the performance of different internal lattice structures (Octet and IsoTruss principally). The purpose of this study is to extend the definition from a discrete (lattice) model to an analytical one for its use in subsequent design phases, capable of optimizing the type of cell to be used and its defining parameters to find the best stiffness-to-weight ratio.
Design/methodology/approach
The representative function of their mechanical behavior is extrapolated through a two-variable polynomial model based on the cell size and the thickness of the beam elements characterizing it. The polynomial is obtained thanks to several tests performed according to the scheme of RSM. An analysis on the estimation errors due to discontinuities in the physical specimens is also conducted. Physical tests applied to the specimens showed some divergences from the virtual (ideal) behavior of the specimens.
Findings
The study allowed to validate the RSM models proposed to predict the behavior of the system as the size, thickness and type of cells vary. Changes in stiffness and weight of specimens follow linear and quadratic models, respectively. This generally allows to find optimal design points where the stiffness-to-weight ratio is at its highest.
Originality/value
Although the literature provides numerous references to studies characterizing and parameterizing lattice structures, the industrial/practical applications concerning lattice structures are often still detached from theoretical research and limited to achieving functioning models rather than optimal ones. The approach here described is also aimed at overcoming this limitation. The software used for the design is nTop. Subsequent three-point bending tests have validated the reliability of the model derived from the method’s application.
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Nicola Cobelli and Silvia Blasi
This paper explores the Adoption of Technological Innovation (ATI) in the healthcare industry. It investigates how the literature has evolved, and what are the emerging innovation…
Abstract
Purpose
This paper explores the Adoption of Technological Innovation (ATI) in the healthcare industry. It investigates how the literature has evolved, and what are the emerging innovation dimensions in the healthcare industry adoption studies.
Design/methodology/approach
We followed a mixed-method approach combining bibliometric methods and topic modeling, with 57 papers being deeply analyzed.
Findings
Our results identify three latent topics. The first one is related to the digitalization in healthcare with a specific focus on the COVID-19 pandemic. The second one groups up the word combinations dealing with the research models and their constructs. The third one refers to the healthcare systems/professionals and their resistance to ATI.
Research limitations/implications
The study’s sample selection focused on scientific journals included in the Academic Journal Guide and in the FT Research Rank. However, the paper identifies trends that offer managerial insights for stakeholders in the healthcare industry.
Practical implications
ATI has the potential to revolutionize the health service delivery system and to decentralize services traditionally provided in hospitals or medical centers. All this would contribute to a reduction in waiting lists and the provision of proximity services.
Originality/value
The originality of the paper lies in the combination of two methods: bibliometric analysis and topic modeling. This approach allowed us to understand the ATI evolutions in the healthcare industry.
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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…
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.