Search results

Knowledge often is the fundament for strategic competitive advantage. Thus, it is highly relevant to understand better how knowledge is transferred from one generation to the next in family businesses. The purpose of this paper is to link the competitive advantage realisation in family businesses to the success of transferring strategically valuable knowledge in different business environments to the next generation.

Building on the contingency model of family business succession (Royer et al., 2008) knowledge transfer in family businesses from different cultures is investigated in this paper. From a resource-oriented and transaction cost inspired perspective two family businesses with a similar industry background from China and Europe are compared regarding knowledge transfer in the context of family firm succession taking into account the respective transaction atmosphere.

Different successions for two long-lived family firms are illustrated in a systematic fashion: based on the theoretical elements suggested both cases are described to get insights into the usefulness of the theoretical reasoning developed. On the basis of these, the cases are compared with each other and conclusions for both cases are drawn. Implications for theory and practice as well as avenues for future research are sketched.

The focus of the current study is to gain more insight into long-lived family businesses by comparing two cases over a period of more than 200 years with regard to strategically relevant resources as well as the underlying transaction atmospheres. Implications for family firms depending on the resource types and transaction atmosphere are discussed.

Excellent obstacle surmounting performance is essential for the robotic vehicles in uneven terrain. However, existing robotic vehicles depend on complex mechanisms or control algorithms to surmount an obstacle. Therefore, this paper aims to propose a new simple configuration of an all-terrain robotic vehicle with eight wheels including four-swing arms.

This vehicle is driven by distributed hydraulic motors which provide high mobility. It possesses the ability to change the posture by means of cooperation of the four-swing arms. This ensures that the vehicle can adapt to complex terrain. In this paper, the bionic mechanism, control design and steering method of the vehicle are introduced. Then, the kinematic model of the center of gravity is studied. Afterward, the obstacle surmounting performance based on a static model is analyzed. Finally, the simulation based on ADAMS and the prototype experiment is carried out.

The experiment results demonstrate that the robotic vehicle can surmount an obstacle 2.29 times the height of the wheel radius, which verifies the feasibility of this new configuration. Therefore, this vehicle has excellent uneven terrain adaptability.

This paper proposes a new configuration of an all-terrain robotic vehicle with four-swing arms. With simple mechanism and control algorithms, the vehicle has a high efficiency of surmounting an obstacle. It can surmount a vertical obstacle 2.29 times the height of the wheel radius.

The authors proposed a new method of fast time delay measurement for integrated pulsar pulse profiles in X-ray pulsar-based navigation (XNAV). As a basic observation of exact orientation in XNAV, time of arrival (TOA) can be obtained by time delay measurement of integrated pulsar pulse profiles. Therefore, the main purpose of the paper is to establish a method with fast time delay measurement on the condition of limited spacecraft’s computing resources.

Given that the third-order cumulants can suppress the Gaussian noise and reduce calculation to achieve precise and fast positioning in XNAV, the proposed method sets the third-order auto-cumulants of standard pulse profile, the third-order cross-cumulants of the standard and the observed pulse profile as basic variables and uses the cross-correlation function of these two variables to estimate the time delay of integrated pulsar pulse profiles.

The proposed method is simple, fast and has high accuracy in time delay measurement for integrated pulsar pulse profiles. The result shows that compared to the bispectrum algorithm, the method improves the precision of the time delay measurement and reduced the computation time significantly as well.

To improve the performance of time delay estimation in XNAV systems, the authors proposed a novel method for XNAV to achieve precise and fast positioning.

Compared to the bispectrum algorithm, the proposed method can improve the speed and precision of the TOA’s calculation effectively by using the cross-correlation function of integrated pulsar pulse profile’s third-order cumulants instead of Fourier transform in bispectrum algorithm.

The Chinese housing market has witnessed rapid growth during the past decade and the significance of housing price forecasting has undoubtedly elevated, becoming an important issue to investors and policymakers. This study aims to examine neural networks (NNs) for office property price index forecasting from 10 major Chinese cities for July 2005–April 2021.

The authors aim at building simple and accurate NNs to contribute to pure technical forecasts of the Chinese office property market. To facilitate the analysis, the authors explore different model settings over algorithms, delays, hidden neurons and data-spitting ratios.

The authors reach a simple NN with three delays and three hidden neurons, which leads to stable performance of about 1.45% average relative root mean square error across the 10 cities for the training, validation and testing phases.

The results could be used on a standalone basis or combined with fundamental forecasts to form perspectives of office property price trends and conduct policy analysis.

The purpose of this study is to make property price forecasts for the Chinese housing market that has grown rapidly in the last 10 years, which is an important concern for both government and investors.

This study examines Gaussian process regressions with different kernels and basis functions for monthly pre-owned housing price index estimates for ten major Chinese cities from March 2012 to May 2020. The authors do this by using Bayesian optimizations and cross-validation.

The ten price indices from June 2019 to May 2020 are accurately predicted out-of-sample by the established models, which have relative root mean square errors ranging from 0.0458% to 0.3035% and correlation coefficients ranging from 93.9160% to 99.9653%.

The results might be applied separately or in conjunction with other forecasts to develop hypotheses regarding the patterns in the pre-owned residential real estate price index and conduct further policy research.

Social engineering is a prominent aspect of online crime. Various interventions have been developed to reduce the success of this type of attacks. This paper aims to investigate if interventions can help to decrease the vulnerability to social engineering attacks. If they help, the authors investigate which forms of interventions and specific elements constitute success.

The authors selected studies which had an experimental design and rigorously tested at least one intervention that aimed to reduce the vulnerability to social engineering. The studies were primarily identified from querying the Scopus database. The authors identified 19 studies which lead to the identification of 37 effect sizes, based on a total sample of N = 23,146 subjects. The available training, intervention materials and effect sizes were analysed. The authors collected information on the context of the intervention, the characteristics of the intervention and the characteristics of the research methodology. All analyses were performed using random-effects models, and heterogeneity was quantified.

The authors find substantial differences in effect size for the different interventions. Some interventions are highly effective; others have no effect at all. Highly intensive interventions are more effective than those that are low on intensity. Furthermore, interventions with a narrow focus are more effective than those with a broad focus.

The results of this study show differences in effect for different elements of interventions. This allows practitioners to review their awareness campaigns and tailor them to increase their success.

The authors believe that this is the first study that compares the impact of social engineering interventions systematically.

This paper seeks to analyse whether the firm model of employment relationships is associated with functional flexibility and organisational learning (exploratory versus exploitative). It also aims to assess the mediating effect of functional flexibility in the relationship between a specific employment mode (mutual investment) and organisational learning.

This research was conducted using a sample of Spanish companies in the food industry, from which data from HR managers and production managers in each firm were collected. Cluster analyses, MANOVA and regression analyses were applied to test the hypotheses.

The results suggest that those firms developing a mutual investment employment relationship outperform other firms in terms of functional flexibility and organisational learning (both exploitative and exploratory learning). The paper also finds a mediating effect of one dimension of functional flexibility (range‐number of activities) between mutual investment and exploitative learning.

The principal limitation of this paper is the cross‐sectional study design, because the dynamic character of learning would require a longitudinal study design. The main research implications are derived from the combination of employment relationships, variety of dimensions of flexibility and learning, and identification of a model of direct and mediating effects among variables.

The results of this paper suggest that a model of employment relationships (mutual investment) favours not only functional flexibility but also ambidextrous learning. Thus, the findings not only provide a broader understanding of the variables associated with HRM, employment relationships and/or flexibility, but also reinforce the strategic role of HRM through its contribution to the development of such a relevant organisational capability that learning represents.

The paper combined a series of variables that previous studies have rarely treated in combination: employment relationships, functional flexibility and exploitative versus exploratory learning. This paper also discusses different dimensions of functional flexibility (range‐number of activities, heterogeneity, mobility, and uniformity), demonstrating the association of some of these dimensions with exploratory or exploitative learning.

The Chinese housing market has gone through rapid growth during the past decade, and house price forecasting has evolved to be a significant issue that draws enormous attention from investors, policy makers and researchers. This study investigates neural networks for composite property price index forecasting from ten major Chinese cities for the period of July 2005–April 2021.

The goal is to build simple and accurate neural network models that contribute to pure technical forecasts of composite property prices. To facilitate the analysis, the authors consider different model settings across algorithms, delays, hidden neurons and data spitting ratios.

The authors arrive at a pretty simple neural network with six delays and three hidden neurons, which generates rather stable performance of average relative root mean square errors across the ten cities below 1% for the training, validation and testing phases.

Results here could be utilized on a standalone basis or combined with fundamental forecasts to help form perspectives of composite property price trends and conduct policy analysis.

This study aims to examine disparities in the code of silence between rural and urban police officers in China.

Data were collected from a national police university in China in 2017. In total, 608 Chinese police officers were surveyed, all of whom attended the in-service training program at the university.

Results suggest that rural officers in China are more likely to embrace the code of silence than their urban counterparts. Additionally, this study demonstrates significant influences of such organizational and environmental factors as police type, agency location and perception of misconduct seriousness on adherence to the code of silence.

This study used a convenient sampling approach, which restricts the generalizability of the results.

Given the stronger code of silence among rural officers, there should be more efforts devoted to cultivating a positive ethical climate within rural police organizations. These efforts may need to come from higher levels of government, given the administrative structure in China. In addition, police supervisors in rural agencies should play an important role, given that they are the first line of defense in detecting and responding to misconduct, and are essential in fostering and sustaining a good ethical environment within the police agency.

Using unique policing data collected from China, this study addresses an important gap in the literature regarding research on rural-urban differences in the police code of silence.

The current study aims to develop a comprehensive hierarchical model of traits and needs to provide a theoretical understanding of personality determinants of luxury-services consumption.

The sample comprised 415 single-event buyers of premium seats in sports stadiums. The causal relationships of hierarchically ordered four traits – elemental, compound, situational and surface – were examined.

Extraversion was found to be an important trait for needs for material resources and status, while conscientiousness and openness were important predictors of need for arousal. Furthermore, needs for material resources, status and uniqueness were found to be important for self-value consciousness. Self-value consciousness was found to be an important predictor of purchase intention.

The study integrates fragmented luxury services research on individual differences. The findings about the personality determinants would provide relatively consistent predictions behind luxury-services consumption potentially applicable to diverse luxury markets.