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To effectively meet their social objectives, humanitarian organizations need to be more innovative and find novel ways to stay competitive. Yet there has been limited focus on innovation by humanitarian organizations. Part of the issue is the lack of new practices and novel approaches that can be used as benchmarks. This study focuses on food banks, a critical hub for the delivery of food in humanitarian supply chains and where the use of innovation seems to be more reported on.

Focusing on resource scarcity, a commonly referenced constraint by humanitarian organizations, the authors study how food and fund scarcity (versus abundance) influence the innovation efforts of twelve food banks in the United States. This study observes variations in behavior before and during the coronavirus disease 2019 (COVID-19) pandemic.

The authors find that food banks operating in high resource scarcity (food-scarce and fund-scarce) settings focus on process innovations. Food banks operating in low resource scarcity (food-abundant and fund-abundant) settings focus on product innovations. Food banks operating in food-abundant and fund-scarce settings focus on marketing innovations. Food banks operating in food-scarce and fund-abundant settings show the most extensive focus on innovation by relying on imitative innovations. The innovation focus for most food banks switches to process innovation during the COVID pandemic.

The study breaks down resource scarcity specific to food banks by differentiating food and funds, a novel approach to studying scarcity. Findings are novel as they suggest that operating context has a highly differentiating effect on what food banks focus on in terms of innovation. Operating context can lead to focus on process, product, imitative of market-related innovations. Finally, the study is novel because it explores how change in the environmental context due to disruptions can drastically modify the innovation focus of food banks.

The purpose of this study is to simultaneously investigate a comprehensive analysis of the extent to which strategic orientations, namely, imitation and innovation orientations, and knowledge management affect firm performance.

Drawing on the theoretical frameworks of the resource-based view and dynamic capability theory, this scholarly inquiry has proposed a comprehensive framework that delineates the relationships amongst imitation, innovation, absorptive capacity (ACAP), innovation performance and financial performance. To scrutinize the proposed research model, bootstrap routines were used through Smart partial least squares to estimate the procedures. To collect the necessary data, a questionnaire and financial statements were acquired from a sample of 100 Iranian firms listed on the Tehran Stock Exchange. The findings of the study have important implications for both scholars and practitioners seeking to enhance firm performance through the effective utilization of imitation, innovation and ACAP.

The results indicate that imitation activities have directly led to the improvement in innovation performance, even in the presence of innovation and ACAP. However, the relationship has not been confirmed by financial performance.

Imitation and innovation orientations have been identified as pivotal strategic orientations that can significantly affect firm performance. As far as the authors know, this investigation represents the first comprehensive examination of both imitation and innovation activities as a critical transition in emerging markets (EMs) characterized by complex economies, such as Iran. The findings may aid firms in enhancing their performance by providing insight into the strategic importance of imitation and innovation orientations in EMs.

This study empirically examines the nonlinear effects of mimicking peer firms' cash holdings on shareholder value, with consideration of macroeconomic conditions.

An instrumental variable approach for nonlinear models is estimated for a large sample of US firms over the period 1991–2019. This approach addresses the reflection problem in examining peer effects, whereby it is impossible to separate the individual's effects on the group, or vice versa, if both are simultaneously determined.

The authors find an inverted U-shaped association between shareholder value and mimicking intensity of peer firms' cash holdings. This result suggests that mimicking peer firms' cash holdings is subject to diminishing returns. It is more beneficial at lower levels of mimicking intensity but less so or suboptimal at higher levels. Further evidence indicates that this inverted U-shaped shareholder value-mimicking intensity nexus is asymmetric. Specifically, it is salient for decreases relative to increases in cash holdings and, more importantly, in good relative to bad macroeconomic states. The findings are robust to several concerns and have important implications for liquidity management policies.

The authors provide new empirical evidence of the nonlinear effects of mimicking peer firms' cash holdings on shareholder value, which varies with macroeconomic conditions.

Women-led enterprises can count on intellectual capital (IC) to implement a knowledge exchange process, improve managerial skills and provide themselves with more certain and reasonable financial resources. Recently, the literature has recognized a new paradigm of innovation, known as open innovation (OI) that emphasizes the strategic importance of relationships for knowledge development. The paper, first, aims to investigate if IC can support female agri-start-ups’ innovation process. Second, the aim is to analyse the ways in which IC supports female agri-start-ups.

The work uses a qualitative methodology and a multiple case study supports the paper. Data were acquired using direct semi-structured interviews. To read and interpret them, the authors resorted to the C.A.O.S. model that permits examining the direct relationships in terms of relational capital (RC) and also, observing the effect produced by the relational circuit in terms of human capital (HC) and structural capital (SC) in small and medium enterprises.

Findings reveal that RC plays a fundamental role in innovative start-up's development. The S-C and S-O links support business management and help fill the gender financial gap. This leads to improving entrepreneurial skills (HC) and promoting internal innovative solutions (SC). The S-A links can help the entrepreneur acquire more awareness of the market and compete better.

The research contributes to IC and gender studies, with a specific focus on RC and the innovation process. Although the literature has already investigated the role of RC in female entrepreneurship, only few previous research have conducted a qualitative analysis about the relationships established in the peculiar context of innovative agri-start-ups.

This research aims to examine the effects of corporate digital transformation on firm value, with a particular focus on the mediating roles played by cost leadership and differentiation strategies.

This study employs word frequency analysis to create corporate digital transformation indicators and determine how corporate digital transformation impacts firm value. The data used in the analysis comes from 2,056 listed manufacturing enterprises in China between 2010 and 2019.

This study demonstrates that digital transformation has a favorable impact on firm value, and that cost leadership strategy and differentiation strategy significantly mediate the relationship between both of them.

This study utilized word frequency analysis to assess the state of corporate digital transformation. It lacked a more thorough description of internal production processes, operational efficiency, and the pace of digital transformation.

The results of this study can not only promote the digital transformation and firm value, but also provide a theoretical basis for enterprises to choose a reasonable competitive strategy in the digital transformation.

This study contributes significantly to the field of firm value research by including digital transformation as a fundamental component. Furthermore, it investigates how cost leadership strategy and differentiation strategy play mediating roles, providing a new perspective and explanatory mechanism for understanding the influence of digital transformation on firm value.

Within the current institutional landscape, characterized by increased societal and governmental emphasis on environmental preservation, there is growing interest in the potential of digital transformation (DT) to advance the circular economy (CE). Nonetheless, the empirical substantiation of the connection between DT and CE remains limited. This study seeks to investigate the impact of DT on CE at the organizational level and examine how various institutional factors may shape this relationship within the Chinese context.

To scrutinize this association, we construct a research framework and formulate hypotheses drawing on institutional theory, obtaining panel data from 238 Chinese-listed high-tech manufacturing firms from 2006 to 2019. A regression analysis approach is adopted for the sample data.

Our regression analysis reveals a positive influence of DT on CE performance at the organizational level. Furthermore, our findings suggest that the strength of this relationship is bolstered in the presence of heightened regional institutional development and industry competition. Notably, we find no discernible effect of a firm’s political connections on the DT–CE performance nexus.

This study furnishes empirical evidence on the relationship between DT and CE performance. By elucidating the determinants of this relationship within the distinct context of Chinese institutions, our research offers theoretical and practical insights, thus laying the groundwork for subsequent investigations into this burgeoning area of inquiry.

In response to mounting global concerns about climate change and scarcity of natural resources, manufacturers have been pressured to develop strategies and enhance their sustainability performance. The integration of sustainable lean manufacturing (SLM) during value chain processes could balance environmental, social and economic concerns into their decision-making, which not only ensures responsible practices but also drives efficiency and success. This paper aims to identify, measure and prioritize metrics to develop a performance measurement system that assesses the multi-dimensional performance of SLM.

Strategic decision-making has some conflicting criteria and objectives to be considered simultaneously. The Multi-Criteria Decision Making provides a foundation for selecting, sorting and prioritizing these strategies with the determination of drivers and indicator weight.

The performance model enables the decision-makers to consistently evaluate the level of sustainability through a multidimensional framework, which could support the assessment of the existing sustainability of a manufacturing process and analyze opportunities for improvement. This study divided the performance into five drivers: Quality, Operational, Finance, Environment, Safety and People and selected 17 KPIs for assessing the multi-dimensional performance of SLM organizations. The research results revealed an organization's perspective transition from strategies focused on operational and economic performance to a more sustainable ideal with greater importance for social and environmental directions.

This framework will be facilitated by the selection of the most significant drivers and the development of strategic plans for the successful adoption of sustainable manufacturing. The practices support implementation, pursue competitive advantages and sustain manufacturing, meeting strategic requirements of suitable and lean performance. With the limited resources of the organizations, the framework proposed will guide the priorities and actions to be taken toward the SLM.

This paper aim to solve the problem of low assembly success rate for 3c assembly lines designed based on classical control algorithms due to inevitable random disturbances and other factors,by incorporating intelligent algorithms into the assembly line, the assembly process can be extended to uncertain assembly scenarios.

This work proposes a reinforcement learning framework based on digital twins. First, the authors used Unity3D to build a simulation environment that matches the real scene and achieved data synchronization between the real environment and the simulation environment through the robot operating system. Then, the authors trained the reinforcement learning model in the simulation environment. Finally, by creating a digital twin environment, the authors transferred the skill learned from the simulation to the real environment and achieved stable algorithm deployment in real-world scenarios.

In this work, the authors have completed the transfer of skill-learning algorithms from virtual to real environments by establishing a digital twin environment. On the one hand, the experiment proves the progressiveness of the algorithm and the feasibility of the application of digital twins in reinforcement learning transfer. On the other hand, the experimental results also provide reference for the application of digital twins in 3C assembly scenarios.

In this work, the authors designed a new encoder structure in the simulation environment to encode image information, which improved the model’s perception of the environment. At the same time, the authors used the fixed strategy combined with the reinforcement learning strategy to learn skills, which improved the rate of convergence and stability of skills learning. Finally, the authors transferred the learned skills to the physical platform through digital twin technology and realized the safe operation of the flexible printed circuit assembly task.

Based on the socio-emotional wealth and agency theories, this study empirically investigates the impact of family ownership and management on green innovation (GI) in family businesses, as well as the moderating effects of institutional environmental support factors, namely, the technological achievement marketisation index and the market-rule-of law index.

This study empirically tests the hypotheses based on a sample of listed Chinese family companies with A-shares in 14 heavily polluting industries from 2009 to 2019.

There is a U-shaped relationship between the percentage of family ownership and GI, and an inverted U-shaped relationship between the degree of family management and GI. Additionally, different institutional environmental support factors affect these relationships in different ways. As the technological achievement marketisation index increases, the U-shaped relationship between the percentage of family ownership and GI becomes steeper, while the inverted U-shaped relationship between the degree of family management and GI becomes smoother. The market rule-of-law index weakens the U-shaped relationship between family ownership and GI.

First, the authors enrich the research on the driving factors of GI from the perspective of the most essential heterogeneity of family businesses. This study shows nonlinear and opposite effects of family ownership and management on GI in family firms. Second, this study contributes to the literature on family firm innovation. GI, not considered by researchers, is regarded as an important deficiency in research on innovation in family businesses. Therefore, this study fills that gap. Third, the study expands research on moderating effects in the literature on GI from the perspective of institutional environmental support factors.

Imitation learning is a powerful tool for planning the trajectory of robotic end-effectors in Cartesian space. Present methods can adapt the trajectory to the obstacle; however, the solutions may not always satisfy users, whereas it is hard for a nonexpert user to teach the robot to avoid obstacles in time as he/she wishes through demonstrations. This paper aims to address the above problem by proposing an approach that combines human supervision with the kernelized movement primitives (KMP) model.

This approach first extracts the reference database used to train KMP from demonstrations by using Gaussian mixture model and Gaussian mixture regression. Subsequently, KMP is used to modulate the trajectory of robotic end-effectors in real time based on feedback from its interaction with humans to avoid obstacles, which benefits from a novel reference database update strategy. The user can test different obstacle avoidance trajectories in the current task until a satisfactory solution is found.

Experiments performed with the KUKA cobot for obstacle avoidance show that this approach can adapt the trajectories of the robotic end-effector to the user’s wishes in real time, including trajectories that the robot has already passed and has not yet passed. Simulation comparisons also show that it exhibits better performance than KMP with the original reference database update strategy.

An interactive learning approach based on KMP is proposed and verified, which not only enables users to plan the trajectory of robotic end-effectors for obstacle avoidance more conveniently and efficiently but also provides an effective idea for accomplishing interactive learning tasks under constraints.