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Modern meat processing requires automation and robotisation to remain sustainable and adapt to future challenges, including those brought by global infection events. Automation of all or many processes is seen as the way forward, with robots performing various tasks instead of people. Meat cutting is one of these tasks. Smart novel solutions, including smart knives, are required, with the smart knife being able to analyse and predict the meat it cuts. This paper aims to review technologies with the potential to be used as a so-called “smart knife” The criteria for a smart knife are also defined.

This paper reviews various technologies that can be used, either alone or in combination, for developing a future smart knife for robotic meat cutting, with possibilities for their integration into automatic meat processing. Optical methods, Near Infra-Red spectroscopy, electrical impedance spectroscopy, force sensing and electromagnetic wave-based sensing approaches are assessed against the defined criteria for a smart knife.

Optical methods are well established for meat quality and composition characterisation but lack speed and robustness for real-time use as part of a cutting tool. Combining these methods with artificial intelligence (AI) could improve the performance. Methods, such as electrical impedance measurements and rapid evaporative ionisation mass spectrometry, are invasive and not suitable in meat processing since they damage the meat. One attractive option is using athermal electromagnetic waves, although no commercially developed solutions exist that are readily adaptable to produce a smart knife with proven functionality, robustness or reliability.

This paper critically reviews and assesses a range of sensing technologies with very specific requirements: to be compatible with robotic assisted cutting in the meat industry. The concept of a smart knife that can benefit from these technologies to provide a real-time “feeling feedback” to the robot is at the centre of the discussion.

Intelligent and connected vehicle technology is in the ascendant. High-level autonomous driving places more stringent requirements on the accuracy and reliability of environmental perception. Existing research works on multitarget tracking based on multisensor fusion mostly focuses on the vehicle perspective, but limited by the principal defects of the vehicle sensor platform, it is difficult to comprehensively and accurately describe the surrounding environment information.

In this paper, a multitarget tracking method based on roadside multisensor fusion is proposed, including a multisensor fusion method based on measurement noise adaptive Kalman filtering, a global nearest neighbor data association method based on adaptive tracking gate, and a Track life cycle management method based on M/N logic rules.

Compared with fixed-size tracking gates, the adaptive tracking gates proposed in this paper can comprehensively improve the data association performance in the multitarget tracking process. Compared with single sensor measurement, the proposed method improves the position estimation accuracy by 13.5% and the velocity estimation accuracy by 22.2%. Compared with the control method, the proposed method improves the position estimation accuracy by 23.8% and the velocity estimation accuracy by 8.9%.

A multisensor fusion method with adaptive Kalman filtering of measurement noise is proposed to realize the adaptive adjustment of measurement noise. A global nearest neighbor data association method based on adaptive tracking gate is proposed to realize the adaptive adjustment of the tracking gate.

The purpose of this paper is to accurately capture the risks which are caused by each road user in time.

The authors proposed a novel risk assessment approach based on the multi-sensor fusion algorithm in the real traffic environment. Firstly, they proposed a novel detection-level fusion approach for multi-object perception in dense traffic environment based on evidence theory. This approach integrated four states of track life into a generic fusion framework to improve the performance of multi-object perception. The information of object type, position and velocity was accurately obtained. Then, they conducted several experiments in real dense traffic environment on highways and urban roads, which enabled them to propose a novel road traffic risk modeling approach based on the dynamic analysis of vehicles in a variety of driving scenarios. By analyzing the generation process of traffic risks between vehicles and the road environment, the equivalent forces of vehicle–vehicle and vehicle–road were presented and theoretically calculated. The prediction steering angle and trajectory were considered in the determination of traffic risk influence area.

The results of multi-object perception in the experiments showed that the proposed fusion approach achieved low false and missing tracking, and the road traffic risk was described as a field of equivalent force. The results extend the understanding of the traffic risk, which supported that the traffic risk from the front and back of the vehicle can be perceived in advance.

This approach integrated four states of track life into a generic fusion framework to improve the performance of multi-object perception. The information of object type, position and velocity was used to reduce erroneous data association between tracks and detections. Then, the authors conducted several experiments in real dense traffic environment on highways and urban roads, which enabled them to propose a novel road traffic risk modeling approach based on the dynamic analysis of vehicles in a variety of driving scenarios. By analyzing the generation process of traffic risks between vehicles and the road environment, the equivalent forces of vehicle–vehicle and vehicle–road were presented and theoretically calculated.

Given the instability and volatility of the labour market and the global talent scarcity, placing more attention on job employability is fundamental. In this context, the literature has already extensively examined employability as a crucial individual aspect, identifying some significant antecedents, including the applicability of training on the job. The present study aims to examine the impact that teaching employees to craft their job may have on the levels of applicability of training and if, in turn, this improves self-perceived employability.

The authors involved three private organizations that followed three workshops on job crafting behaviour. To empirically assess the intervention, the authors asked participants of the workshop to complete four quantitative diaries on a weekly basis, i.e. one per week, one before the intervention and three after the intervention. The diaries comprised measures of job crafting behaviours, applicability of training and self-perceived employability.

Multi-level analysis of data collected provided support to the positive associations between job crafting behaviour and self-perceived employability with the mediating effect of applicability of training. Notably, the applicability of training improves when individuals search for challenges, which indirectly affects perceived employability in terms of organizational sense.

In the present study, no control group was used with which the results of our intervention could be compared. However, this does not affect the overall results, given the amount of intraindividual variability.

The paper proposes initial avenues for promoting employability at work via the use of behavioural job crafting intervention.

This paper aims to identify the relationship between participation motivation, satisfaction and exercise adherence intention of golf range users on the basis of self-determination theory.

For this purpose, the authors proposed research questions and a conceptual research model as well. Then, the authors surveyed users of golf ranges located in Seoul Metropolitan City and Gyeonggi-do province.

By applying convenience sampling, the authors received a total of 313 questionnaires. Results were as follows. First, among the participation motivation sub-factors, health-oriented motivation, achievement motivation, pleasure-oriented motivation and self-displayed motivation had a significant effect on emotional satisfaction, while achievement motivation and pleasure-orientation motivation had a significant effect on performance satisfaction. Second, the following participation motivation factors had a significant effect on exercise adherence intention: health-orientation motivation, achievement motivation and pleasure-orientation motivation. Third, among the satisfaction factors, emotional satisfaction and performance satisfaction both had a significant effect on exercise adherence intention.

This is one of the first papers to examine the relationships that exist between golf range users’ participation motivation, satisfaction and exercise adherence intention.

This study aims to propose an offline exploratory method that consists of two stages: first, the authors focus on completing the kinematics model of the system by analyzing the Jacobians in the vicinity of the starting point and deducing a virtual input to effectively navigate the system along the non-holonomic constraint. Second, the authors explore the sensorimotor space in a predetermined pattern and obtain an approximate mapping from sensor space to chained form that facilitates controllability.

In this paper, the authors tackle the controller acquisition problem of unknown sensorimotor model in non-holonomic driftless systems. This feature is interesting to simplify and speed up the process of setting up industrial mobile robots with feedback controllers.

The authors validate the approach for the test case of the unicycle by controlling the system with time-state control policy. The authors present simulated and experimental results that show the effectiveness of the proposed method, and a comparison with the proximal policy optimization algorithm.

This research indicates clearly that feedback control of non-holonomic systems with uncertain kinematics and unknown sensor configuration is possible.

The aim of this study is to explore the contextual influences of packaging design and its cues on respondents' preferences.

To explore the contextuality of packaging cues, a multi-attribute valuation technique, conjoint analysis was used for two types of pharmaceutical products (painkiller and sore throat medicine) across seven countries. Data were collected among respondents (N = 461) from Finland, Ghana, Mongolia, Nigeria, Portuguese, South Africa and the USA.

Similarities and dissimilarities were observed between the product types and countries analysed in terms of the impact of packaging cues. The findings demonstrate the global and local nature of brand cues expressed in retail packaging.

The study implies that some cues may serve global markets, while some cues may need to be localised in order to meet the needs of local markets. Understanding these cues and their influences on consumers' brand preferences and choices at the point-of-purchases may enable companies to enter new markets, help them create sustainable and credible global brands.

The study contributes to the existing retail packaging literature and pharmaceutical branding literature by providing empirical evidence of the multidimensional aspects of sensory packaging cues. Second, it contributes by showing the contextual nature of retail packaging and its associated cues for OTC pharmaceuticals.

The major objective of the study is to investigate the effect of selected customer retention strategies (fair pricing, online marketing and frequent communication) on perceived service quality and organisational performance within the retail sector in Zimbabwe. Also, the study sought to understand the moderating role of ICT on the effect of customer retention strategies on perceived service quality and organisational performance.

A cross-sectional survey of 280 employees within Zimbabwe's retail sector was adopted and respondents were selected using simple random sampling method. A structured questionnaire with Likert type questions was used to gather data.

The study findings indicate that the performance of organisations within the retail sector is influenced by superior service quality, selected customer retention strategies and also moderated by the use of ICT.

The study contributes to the business management body of knowledge by assessing the effect of selected customer retention strategies (fair pricing, online marketing and frequent communication) on perceived service quality and organisational performance within the retail industry of an emerging economy. The study is also unique in that it used ICT to moderate the effect of selected customer retention strategies on perceived service quality and organisational performance.

The empirical study of factors related to digital transformation (DT) in the banking sector is still limited, even though the importance of the topic is universally evident. To bridge that gap, this paper aims to explore the role of digital leadership (DL), innovative culture (IC) and technostress inhibitors (TI) to support engagement for improved digital innovation (DI). Based on the literature, these variables are crucial aspects of digitalisation, even though there is no agreement on their conclusiveness.

This quantitative study tested a new conceptual model using survey data from five major banks in Libya. Partial least squares structural equation modelling was used to analyse the data from the 292 usable responses.

The results showed that DL and IC positively affect DI. Techno-work engagement (TE) mediated the relationship between leadership, culture and innovation. TI played a significant moderating role in leadership, culture and engagement relationships.

The research findings highlight critical issues about how leadership style and fostering organisational support in the banking sector can enhance DT. Leaders must demonstrate a commitment to long-term resource allocation to avoid possible negative effects from digital stress while pursuing DI through work engagement.

The study suggests that fostering organisational support can enhance DT in retail banks, potentially leading to improved customer experiences and increased access to financial services. These programs will help banks contribute to societal and economic development.

This timely study examines predictor mechanisms of innovation in retail banking that resonate within the restrictions of organisational and DI frameworks and the social exchange theory. Exploring the intervening effect of TE in the leadership, culture and innovation associations is unprecedented.

The purpose of this paper is to postulate that the technique of Importance-Performance Analysis (IPA) is currently underutilised in visitor management studies reported in the peer-reviewed marine wildlife tourism (MWT) research literature. Further, this paper provides insight into how IPA could inform future research and management of tourism experiences at marine wildlife destinations.

This paper synthesises learning gained from the natural area tourism and recreation literature that report the application of IPA in MWT and insights from a recent study at the Dolphin Discovery Centre in Bunbury, Western Australia.

Although currently underutilized in MWT research, IPA is a relatively straightforward, easy to interpret, and, if correctly applied, a powerful tool that managers and researchers can employ to investigate and enhance visitor satisfaction in the short-term and for longer-term sustainability of the industry through visitor-informed tourism management.

Having identified the opportunity to enhance visitor experiences, site management and target species welfare through increased IPA research, this review provides a plain language introduction to the application of IPA and direct access to comprehensible academic discourses and exemplars for the technique. Moreover, in light of increasing tourism demand, IPA can assist in determining management options for the future.