Search results

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.

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.

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.

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.

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.

To combat climate change, protect biodiversity, maintain water quality, facilitate a just transition for workers and engage citizens and communities, a diversity of stakeholders across multiple levels work together and collaborate to co-create mutually beneficial solutions. This paper aims to illustrate how a 7.5-year collaboration between local communities, researchers, academics, companies, state agencies and policymakers is contributing to the reframing of industrial harvested peatlands to regenerative ecosystems and carbon sinks with impacts on ecological, economic, social and cultural systems.

The European Union LIFE Integrated Project, Peatlands and People, responding to Ireland’s Climate Action Plan, represents Europe’s largest rehabilitation of industrially harvested peatlands. It makes extensive use of marketing research for reframing strategies and actions by partners, collaborators and communities in the evolving context of a just transition to a carbon-neutral future.

The results highlight the ecological, economic, social and cultural reframing of peatlands from fossil fuel and waste lands to regenerative ecosystems bursting with biodiversity and climate solution opportunities. Reframing impacts requires muddling through the ebbs and flows of planned, possible and unanticipated change that can deliver benefits for peatlands and people over time.

At 3 of 7.5 years into a project, the authors are muddling through how ecological reframing impacts economic and social/cultural reframing. Further impacts, planned and unplanned, can be expected.

This paper shows how an impact planning canvas tool and impact taxonomy can be applied for social and systems change. The tools can be used throughout a project to understand, respond to and manage for unplanned events. There is constant learning, constantly going back to the impact planning canvas and checking where we are, what is needed. There is action and reaction to each other and to the diversity of stakeholders affected and being affected by the reframing work.

This paper considers how systemic change through ecological, economic, social and cultural reframing is a perfectly imperfect process of muddling through which holds the promise of environmental, economic, technological, political, social and educational impacts to benefit nature, individuals, communities, organisations and society.

The need to digitise is an awareness that is shared across our community globally, and yet the probability of the intersection between resources, expertise and institutions are not as prospective. A strategic view towards the long-term goal of cultivating and digitally upskilling the younger generation, building a community and creating awareness with digital activities that can be beneficial for cultural heritage is necessary.

The work involves distributing tasks between stakeholders and local volunteers. It uses close-range photogrammetry for reconstructing the entire heritage site in 3D, and outlines achievable digitisation activities in the crowdsourced, close-range photogrammetry of a 19th century Cheah Kongsi clan temple located in George Town, a UNESCO World Heritage Site in Penang, Malaysia.

The research explores whether loosely distributing photogrammetry work that partially simulates an unorganised crowdsourcing activity can generate complete models of a site that meets the criteria set by the needs of the clan temple. The data acquired were able to provide a complete visual record of the site, but the 3D models that was generated through the distributed task revealed gaps that needed further measurements.

Key lessons learned in this activity is transferable. Furthermore, the involvement of volunteers can also raise awareness of ownership, identity and care for local cultural heritage.

Key lessons learned in this activity is transferable. Furthermore, the involvement of volunteers can also raise awareness of identity, ownership, cultural understanding, and care for local cultural heritage.

The value of semi-formal activities indicated that set goals can be achieved through crowdsourcing and that the new generation can be taught both to care for their heritage, and that the transfer of digital skills is made possible through such activities. The mass crowdsourcing activity is the first of its kind that attempts to completely digitise a cultural heritage site in 3D via distributed activities.

Automation and the new buzzword, “Industry 4.0”, have dominated the media headlines in recent months. In this scenario, apparel manufacturers should not only install automatic machines but also standardise them based on specific industry requirements, and precise measures are required for daily target demands.

This study demonstrates the application of Predetermined Motion and Time System (PMTS) tools in various automatic and semiautomatic machines to obtain higher productivity and the highest utilisation percentage of operator and automats between the 1:1 and 1:2 man vs machine configuration models. In this study, timeSSD® was used to calculate the micro motions of humans. In addition, a video annotation and modelling software Tracker was used to calculate high-speed machine movements with loading frames of 30 FPS.

After the implementation of PMTS tools, it was found that for a 1:1 man vs machine configuration, the operator utilisation is 75% per shift and the operator idle time is 50% per cycle time, and the operator is sitting idle for 2 h per 8 h of shift. So, there is scope to improve the utilisation and idle time of operator.

With the PMTS software, an industrial engineer professional with knowledge of the micromotion economy can only calculate micromotion.

Exploring the first time in the world to establish standard allowed minute (SAM) of a partly automated single-unit sewing machine with partial human intervention and a semiautomatic machine. Theoretical underpinnings indicate that manufacturers use the experience to determine the SAM of any operation over time, necessitating this work to calculate standard minutes automatically.

Explore how the degree of humanization affects user misconduct, and provide effective misconduct prevention measures for the wide application of artificial intelligence in the future.

Based on the “Uncanny Valley theory”, three experiments were conducted to explore the relationship between the degree of humanization of service machines and user misbehavior, and to analyze the mediating role of cognitive resistance and the moderating role of social class.

There is a U-shaped relationship between the degree of humanization of service machines and user misbehavior; Social class not only regulates the main effect of anthropomorphism on misbehavior, but also regulates the intermediary effect of anthropomorphism on cognitive resistance, thus affecting misbehavior.

The design of the service robot can be from the user’s point of view, combined with the user’s social class, match different user types, and provide the same preferences as the user’s humanoid service robot.

This study is an important reference value for enterprises and governments to provide intelligent services in public places. It can prevent the robot from being vandalized and also provide users with a comfortable human-computer interaction experience, expanding the positive effects of providing smart services by government and enterprises.

This study avoids and reduces users' misbehavior towards intelligent service robots, improves users' satisfaction in using service robots, and avoids service robots being damaged, resulting in waste of government, enterprise and social resources.

From the perspective of product factors to identify the inducing factors of improper behavior, from the perspective of social class of users to analyze the moderating effect of humanization degree and user improper behavior.

This study explores the relationship between economic freedom and gender ideologies on the allocation of women’s opportunity-to-necessity entrepreneurship across countries. Opportunity entrepreneurship is typically understood as one’s best option for work, whereas necessity entrepreneurship describes the choice as driven by no better option for work. Specifically, we examine how economic freedom (i.e. each country’s policies that facilitate voluntary exchange) and gender ideologies (i.e. each country’s propensity for gendered separate spheres) affect the distribution of women’s opportunity-to-necessity entrepreneurship across countries.

We construct our sample by matching data from the following country-level sources: the Global Entrepreneurship Monitor’s Adult Population Survey (APS), the Fraser Institute’s Economic Freedom Index (EFI), the European/World Value Survey’s Integrated Values Survey (IVS) gender equality index, and other covariates from the IVS, Varieties of Democracy (V-dem) World Bank (WB) databases. Our final sample consists of 729 observations from 109 countries between 2006 and 2018. Entrepreneurial activity motivations are measured by the ratio of the percentage of women’s opportunity-driven total nascent and early-stage entrepreneurship to the percentage of female necessity-driven total nascent and early-stage entrepreneurship at the country level. Due to a first-order autoregressive process and heteroskedastic cross-sectional dependence in our panel, we estimate a fixed-effect regression with robust standard errors clustered by country.

After controlling for multiple macro-level factors, we find two interesting findings. First, economic freedom positively affects the ratio of women’s opportunity-to-necessity entrepreneurship. We find that the size of government, sound money, and business and credit regulations play the most important role in shaping the distribution of contextual motivations over time and between countries. However, this effect appears to benefit efficiency and innovation economies more than factor economies in our sub-sample analysis. Second, gender ideologies of political equality positively affect the ratio of women’s opportunity-to-necessity entrepreneurship, and this effect is most pronounced for efficiency economies.

This study offers one critical contribution to the entrepreneurship literature by demonstrating how economic freedom and gender ideologies shape the distribution of contextual motivation for women’s entrepreneurship cross-culturally. We answer calls to better understand the variation within women’s entrepreneurship instead of comparing women’s and men’s entrepreneurial activity. As a result, our study sheds light on how structural aspects of societies shape the allocation of women’s entrepreneurial motivations through their institutional arrangements.