Human-robot interaction (HRI) promises to be a means whereby manufacturing companies will be able to address current challenges like a higher demand for customization. However, despite comparably low ...costs, there are only few applications in practice. To date, it remains unclear which factors facilitate or hinder the successful introduction of industrial collaborative robots (cobots). In a three-step approach, we first developed a comprehensive two-dimensional framework covering three separate phases and four essential components for human-robot working systems. Secondly, we reviewed related literature to identify relevant success factors. Thirdly, in an online survey we asked leading representatives of German manufacturing companies (
n
= 81) to assess the importance of these factors from a practical point of view. The results reveal that besides technology-related factors like occupational safety and appropriate cobot configuration, employee-centered factors like the fear of job loss and ensuring an appropriate level of trust in the robot are considered important. However, company representatives seem to underestimate the impact of subtle measures to increase employee acceptance which could be incorporated into internal communication strategies prior to and during the introduction of cobots. Comparative analysis based on three distinct application scenarios suggests that most success factors’ practical importance is independent of the motivation for implementing HRI. Furthermore, answers from practitioners in free-text fields reveal that success factors which intuitively come to their mind such as financial factors are not necessarily perceived most important. Finally, we argue for more application-oriented research that focuses on practically relevant factors to guide HRI research, inform cobot development, and support companies in overcoming apparent barriers.
Discussions on the potentials and risks of the relocation of manufacturing activities to low-wage countries have resurged in recent years in the wake of a new globalisation debate. Manufacturing ...offshoring has become an increasingly interesting option for firms of all sizes. Besides the chances to improve the company's cost position, the risks of production offshoring are also evident. An analysis of the manufacturing offshoring and backshoring activities of 1663 German manufacturing companies shows that production offshoring has currently lost momentum. On the other hand, backshoring of once offshored manufacturing capacities is also a quantifiable phenomenon. Every fourth to sixth offshoring activity is followed by a backshoring activity within the following 4 years, mainly due to lack of flexibility and quality problems at the foreign location. A deeper, qualitative analysis in 39 German manufacturing companies shows that not all companies do pay sufficient attention to qualitative factors crucial for success and competitive advantage in their location decisions. Thus, managerial implications for a systematic location planning process are drawn from our findings.
Although the implementation of innovative organizational concepts is considered to be highly important for a company's competitiveness, so far there has been little research on possible approaches to ...measure and monitor organizational innovations in large-scale surveys. Based on an item-oriented typology of organizational innovations which serves as the precondition for a common understanding, we describe and compare how organizational innovations have been measured through existing surveys in Europe. Using a large-scale survey comprising data of 1450 German manufacturing companies, we show how these different approaches lead to significantly different results regarding the organizational innovativeness of companies within one and the same sample. We derive four implications for the future measurement and monitoring of organizational innovations. Our findings contribute to the further development of an adequate methodology for an organizational innovation monitoring system.
Purpose
The purpose of this paper is to present an empirical investigation of recent trends and changes in companies' production relocation and backshoring behaviour against the background of the ...global economic crisis.
Design/methodology/approach
The empirical research is based on a large data set of 1,484 German manufacturing companies as part of the European Manufacturing Survey (EMS). The paper employs a structured set of probit analyses to identify the differences of production relocation and backshoring determinants before and within the crisis.
Findings
Against common belief the paper finds that not only the relocation of production to emerging countries, but also the
backshoring
of once offshored manufacturing capacities to the home base is a relevant phenomenon. Since the emergence of the global economic crisis, relocation activities declined significantly, whereas the level of backshoring activities has remained stable. Far‐shore destinations in Asia gain in attractiveness over near‐shore locations in Eastern Europe. Particularly export‐intensive companies tended recently towards (re‐)concentrating of their production capacities, trying to exploit the benefits of higher capacity utilisation and a superior relation of variable costs to fix costs at their existing locations.
Research limitations/implications
Although covering a significant range of industrial sectors in Germany, more empirical evidence is needed from other branches and countries. Looking forward it is proposed to systemically integrate scenarios on the future development of the most influential environmental factors in future research frameworks for global production decisions and value chains.
Practical implications
The findings strongly recommend a revision of established decision‐making schemes for production relocations based on pure cost efficiency considerations. Decision‐making should integrate qualitative environmental factors and dynamic considerations using scenario‐based tools. Companies need to understand and prepare for dynamic developments at different locations which can strategically necessitate backshoring after a certain time.
Originality/value
The research considerably widens the empirical knowledge on recent trends in relocation activities and their inherent risks, which in a dynamic perspective are sometimes forcing backshoring activities.
In this short comment, empirical evidence will be offered to some of the questions Fratocchi et al., 2014. J. Purchasing Supply Manage. 20(1), http://dx.doi.org/10.16/j.pursup.2014.01.004 have posed ...in their short conceptual paper in this issue. Dynamics of German backshoring activities over the past 15 years are described and differences in motivations between the main backshoring modes are depicted. Further implications for global value chains and local manufacturing modes are discussed and future research directions are proposed.
•Dynamics of German backshoring activities over the past 15 years are described.•Differences in motivations between the main backshoring modes are depicted.•The decline of global value chains and the emergence of local manufacturing are discussed.•Research questions on dynamic developments of backshoring strategies are proposed.
In current discussions, Artificial Intelligence (AI) is ascribed great influence on production processes. Research on AI has seen tremendous growth in recent years. However, most of the research has ...focused primarily on various AI technologies, and less on prerequisites and enablers for adoption of AI at firm-level. This is surprising, given the fact that many companies are still struggling to establish AI in their production and to drive their AI adoption forward.
To close this gap, this study analyses the impact of various technological, organizational and environmental (TOE) prerequisites for a successful adoption of AI technologies in manufacturing. Based on a cross-national survey of 655 company representatives from the manufacturing industry, our results contribute to a better understanding of why some companies are more determined than others when it comes to implementing AI in their production. We find evidence that organizational factors, such as digital skills, company size, and R&D intensity, have the greatest impact on the adoption of AI in manufacturing. Furthermore, in order to gain new insights into the interplay of new technology adoption and global production strategies, this paper addresses the question of which factors explain a primarily domestic or globally oriented technology adoption. We find that especially research-intensive, knowledge-based and service-oriented companies tend to roll out AI technologies not only at their domestic but also at their foreign production sites.
•Transnational survey on the current adoption status of AI in the manufacturing industry.•Validation of company characteristics as prerequisites for adopting AI.•Examination of digital skills as the key enabler for AI adoption.•First insights into which companies roll out AI technologies globally or only domestically.
We investigate the relationship between backshoring of production activities and digital manufacturing technologies, also known as Industry 4.0 (I4.0). We argue that I4.0 supports backshoring because ...it provides a higher productivity and flexibility which offers an incentive for firms to locate production close to their European customers.
The empirical test is based on a large dataset of 1700 manufacturing firms from Austria, Germany, and Switzerland. Backshoring is still a rare event with a share of around 4% of all firms. Descriptive statistics as well as regression results indicate a positive correlation between the adoption of I4.0 technologies and companies’ backshoring propensity.
•Linguistic framing provides an effective means for increasing initial trust in collaborative robots•Effects of anthropomorphism on trust are moderated by the human-robot relation (cooperative vs. ...competitive)•Research designs in the industrial context need to consider the psychology of technological replacement•External validity is ensured by recruiting factory workers as an adequate sample for industrial human-robot interaction
An appropriate level of human-robot trust is considered a necessary precondition for successful human-robot interaction (HRI). With collaborative robots (cobots) entering production sites and allowing factory workers to operate interactively, issues of human-robot trust at the workplace are gaining relevance and complexity. It is widely believed that trust is promoted by anthropomorphisation, that is, the application of human-like mental models to technical devices. Anthropomorphisation can be triggered by altering either the characteristics of the robot or the mental models of the human interaction partner, for example by providing linguistically framed descriptions of the robot. However, the research base on linguistic framing effects on anthropomorphisation and on human-robot trust in industrial environments is scarce. This article aims to close this research gap by investigating changes in inexperienced factory workers’ initial trust induced by linguistic framing in the run-up to an interaction. Besides the human-likeness of the robot, the framing also addresses the human-robot relation in order to take into account the special circumstances of cobot use in the industrial workplace. In this usage context, cobots frequently provoke ambivalent attitudes amongst employees, who see themselves in a cooperative or in a competitive relationship to the robot, depending on whether they consider the latter as complementing or substituting their jobs.
The results of the pre-post online experiment presented in this article highlight the effectiveness of framing and reveal a significant interaction effect between perceived human-likeness and cooperativeness. In particular, human-like framing of the cobot significantly increases an employee's trust in the cobot only when the human-cobot relation is perceived as cooperative. This can be explained by different psychological reactions on the anticipated technological replacement by either man or machine. This finding suggests that the way employees relate to cobots represents a relevant contextual factor in the industrial workplace that moderates the effect of anthropomorphisation on human-robot trust. Furthermore, providing information about the cobot generally seems to foster trust, possibly resulting from an effect of imagined contact with the cobot.
•Individual characteristics and the experimental setting (online vs. face-to-face) influence the effectiveness of framing.•Students seem to be less sensitive to linguistic framing of a robot's ...human-likeness than production workers.•Linguistic framing seems to be more powerful in reducing distrust than in fostering trust.•In the context of our study, a short-term interaction with a robot increases trust and reduces distrust significantly, even in erroneous cases.•The experimental design includes a realistic short-term human-robot interaction with a collaborative robot.
An appropriate level of human-robot trust is widely acknowledged as a crucial factor for successful human-robot interaction (HRI). Previous research has addressed anthropomorphic design but mostly neglected linguistic framing as a means to influence trust by altering the perceived human-likeness of a robot. Similarly, time-dependant patterns of trust and distrust during an HRI have rarely been investigated, hindering the development of a coherent theoretical framework on framing effects, their formation conditions, and their relation to trust and distrust evolution in the HRI context. A previous online study suggested that linguistic framing modulates inexperienced factory workers’ trust in a collaborative robot at the workplace. This article presents a follow-up study with a sample of students and an realistic HRI setting. Despite using similar framing stimuli, the study failed to replicate significant framing effects on trust, suggesting their context-sensitivity and dependence on individual characteristics of the recipients of the framing. Additionally, a significant increase in trust and decrease in distrust during the HRI highlights the need for time-dependant considerations. The results call for a more fine-grained investigation of linguistic framing effects as well as of trust and distrust evolution in order to develop a comprehensive theoretical framework applicable to the HRI context.
Artificial intelligence (AI) is considered the next strategic technological imperative as it allows firms to manage complex tasks and to solve problems in many industries. In the manufacturing ...context, the use of AI is affecting the configuration of production processes with possible effects on the location of production activities. Despite the increasing relevance of this technology, there is a lack of empirical evidence that assesses the linkage with the firm's production relocation strategies. To fill this gap, this study aims at exploring the relationship between the use of AI and companies' offshoring and backshoring decisions, taking into account the moderating role of digital competences and the intended internationalisation strategies. Based on a cross-national survey with answers from 676 manufacturing companies from 16 industrialized countries, a hierarchical regression analysis was deployed that shows a positive effect of AI on companies' offshoring and backshoring decisions. Moreover, the results show that digital competences and international ambidexterity (simultaneous expansion of business and supply chain activities in domestic and foreign locations) only have a moderation effect on the relationship between AI and backshoring. International concentration (locating business activities in only a few local or global locations) does not moderate the relationship between AI and production relocation strategies (offshoring or backshoring). To advance the theoretical debate on the use of AI and its impact on production relocation strategies, three research propositions are proposed. Finally, some practical implications and the study's limitations are highlighted.
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