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This paper aims to automate the picking task needed in robotic assembly. Parts supplied to an assembly process are usually randomly staked in a box. If randomized bin-picking is introduced to a production process, we do not need any part-feeding machines or human workers to once arrange the objects to be picked by a robot. The authors introduce a learning-based method for randomized bin-picking.

The authors combine the learning-based approach on randomized bin-picking (Harada et al., 2014b) with iterative visual recognition (Harada et al., 2016a) and show additional experimental results. For learning, we use random forest explicitly considering the contact between a finger and a neighboring object. The iterative visual recognition method iteratively captures point cloud to obtain more complete point cloud of piled object by using 3D depth sensor attached at the wrist.

Compared with the authors’ previous research (Harada et al., 2014b) (Harada et al., 2016a), their new finding is as follows: by using random forest, the number of training data becomes extremely small. By adding penalty to occluded area, the learning-based method predicts the success after point cloud with less occluded area. We analyze the calculation time of the iterative visual recognition. We furthermore make clear the cases where a finger contacts neighboring objects.

The originality exists in the part where the authors combined the learning-based approach with the iterative visual recognition and supplied additional experimental results. After obtaining the complete point cloud of the piled object, prediction becomes effective.

The industrial unrest during January 1988 among nurses in the UK National Health Service raised the matter of the attitude and behaviour of that group of employees towards industrial action. In some circles that action is regarded as “unprofessional”. While the causes are shown to be complex, it is argued that they primarily involve two issues. First there was the threat of a fall in current pay levels and, secondly there was the view taken by those nurses that professional standards of nursing were falling. The nature of the dispute showed how professionalism and industrial action can be reconciled. This is done mainly by a “demonstration” rather than by a “stoppage”, while maintaining full cover of essential duties. A major aim of the action was to mobilise public and media opinion in favour of the nurses′ case.

The purpose of this paper is to develop a planner for finding an optimal assembly sequence for robots to assemble objects. Each manipulated object in the optimal sequence is stable during assembly. They are easy to grasp and robust to motion uncertainty.

The input to the planner is the mesh models of the objects, the relative poses between the objects in the assembly and the final pose of the assembly. The output is an optimal assembly sequence, namely, in which order should one assemble the objects, from which directions should the objects be dropped and candidate grasps of each object. The proposed planner finds the optimal solution by automatically permuting, evaluating and searching the possible assembly sequences considering stability, graspability and assemblability qualities.

The proposed planner could plan an optimal sequence to guide robots to do assembly using translational motion. The sequence provides initial and goal configurations to motion planning algorithms and is ready to be used by robots. The usefulness of the proposed method is verified by both simulation and real-world executions.

The paper proposes an assembly planner which can find an optimal assembly sequence automatically without teaching of the assembly orders and directions by skilled human technicians. The planner is highly expected to improve teachingless robotic manufacturing.

This study aimed to obtain the study results of the visit increase model by adding the word of mouth (WOM) variable based on the results of research reviews in 2017 and 2019. The research was conducted in the ecotourism area of the south coast of West Java, which is oriented toward the environment’s carrying capacity and improving the community’s economy. Data analysis used descriptive verification using structural equation modeling (SEM), with a total of 302 respondents. The study results obtained descriptive analysis results based on research in 2017 and 2019, which showed no different results. The descriptive analysis results show that tourist travel motivation is considered strong by tourists; tourists have felt impressive tourism experiences. The average image of tourism destinations is considered sufficient. The West Java ecotourism area is quite successful in becoming a positive WOM conversation among most tourists. The intention to revisit is considered insufficient, or tourists have not agreed to return soon. The results of the verification analysis show that all the proposed hypotheses have a significant effect so that the model of increasing tourist visits based on travel motivation and impressive tourism experiences, the destination image that is intermediated by the WOM variable, has an impact on revisiting intention.

This chapter explores the concept of branding in a contemporary competitive arena of places. The multi-dimensional interpretations of places offer a variety of possibilities to better understand the true essence of destination branding. One of the common interpretations of places is through the study of their images, as destination branding requires a thorough understanding of destination image. The important foundation and relation of destination image are specified and explained. The notion of destination branding has evolved from the fields of marketing and urban studies and has become a cross-disciplinary research area. Thus, the researchers explain that destination branding as well as ‘place branding’ are dynamic concepts that are being continuously being explored in academia for the benefit of practitioners in travel and tourism. This chapter suggests that the use of brand equity is also one of the frontier areas of study in ‘place branding’ as it emphasises the need to thematise destinations (e.g. for their historical heritage, cultural value, natural attractions, etc.) and places for residence (e.g. as green cities, creative cities, smart cities, etc.).

Tourism is one of the main income generator for the Singapore’s economy. Since China is the second largest tourist group to Singapore in the past 15 years which is due to the newly middle class and the appreciation of Chinese Yuan, this study attempts to explore the market potential by understanding Chinese tourist’s repeat visit intention. A sample of 192 Chinese tourists is collected at Singapore Chiang International Airport to study eight selected satisfaction attributes using systematic random sampling techniques. The mean scores indicate that all attributes are above the average. In addition, transportation and environment/safety are tied as the most satisfactory attribute. Further, a logistic regression model identifies which attributes lead the Chinese tourists’ likelihood to revisit Singapore. Three attributes entailing lodging, attraction and environment and safety, are significant. The managerial implications are also discussed.

Extensive research towards identifying the attributable cost overrun factors globally has been conducted predominantly from a survey-oriented perspective, which disregard the contextual basis on which these triggers manifest. This study aims to explore the driving factors of cost overrun in highway projects, specific to the Nigerian context.

The research used a context-based approach to seek project stakeholders’ perspectives on the key drivers of cost overrun in highway projects in Nigerian. Semi-structured interviews were conducted with client, contractor and consultant organisations involved in the provision of highway infrastructure projects in Nigeria. The collected data was analysed using a developed coding framework grounded on a case study approach, principles of inductive thematic analysis and saliency analysis to identify the key drivers.

Findings from the analysis identified triggers from macroeconomic, societal, leadership and project management perspectives with synergistic relationships with each other based on prevalence and significance. Among the key triggers is a delay in work progress, political instability, adverse weather, social issues, delay in progress payment to contractors and modification of project scope. In conclusion, the triggers of cost overrun in highway projects are contextually driven by the complex nature of the project management, societal, macroeconomic and leadership triggers specific to the Nigerian context.

The research was limited to only highway infrastructure projects in Nigeria. Furthermore, the findings are based on a small sample size, and thus, caution must be taken before applying the outcome of this study in a generalised way to other contexts.

Practically, the stakeholders i.e. client, contractors and consultants should acknowledge the contextual circumstances in which each of the triggers takes place, which will aid in developing pragmatic measures and make the right decisions towards addressing these triggers during any highway construction project in Nigeria and enhance the chances of project success.

The context-based approach applied in this study is expected to provide a new insight in understanding the triggers of cost overruns, especially in highway projects in Nigeria and indeed other developing countries with similar governance characteristics

While internationalization of firms can be a source of growth in profitability, it can also result in huge losses due to the risky internationalized environment. Success in the home countries does not guarantee success internationally. The objective of this study is to identify the main business factors affecting performance of firms in the process of internationalization.

Ten business factors have been selected to investigate their relationship with the business performance in the internationalization process of Chinese manufacturing firms. The ten business factors are transformed into four dimensions (principal factors) using the method of factor analysis. Using the categorical regression method, relationships between return on assets (ROA) and the four dimensions extracted are examined.

The findings reveal that marketing capability of firms plays the most important role in improving performance of firms that embrace internationalization.

The study is confined to data collected from the Yangtze River Delta region via the method of survey, and it is generally agreed that China is a large market composed of distinctively different regional sectors, and there are significant differences in the level of development among the regions.

Performance of firms that embrace internationalization is affected by different business factors. If these factors could be identified, it would be possible to engineer the performance of firms.

From a political perspective, the research provides a better understanding on how to improve the internationalization performance for firms, which do not have such experience in the emerging economies.

The purpose of this paper is to test the validity of dynamic tradeoff theory and argue that the speed of adjustment toward the target capital structure may vary depending primarily on some inherent firm characteristics.

The objective of this article is to study the impact of the corporate governance arrangements on the capital structure behavior taken by listed French firms. The author measures the corporate governance arrangements in three different ways to capture its influences on the capital structure and analyze how it affects a firm's rebalancing behavior in the presence of relevant control variables. Assuming that costs related to deviations from the target leverage are positively correlated with the duration of the deviation, the author finds that firms with a strong governance system adjust at a faster rate because the longer the deviation lasts, the greater the loss in firm value. In addition, firms with more efficient governance structures face lower adjustment costs.

The author measures corporate governance quality in different ways by using several proxies. The results make a major contribution to the literature and show that the quality of the governance system is an important factor in helping the company achieve fatly its target leverage. The authors produces further support for the initial finding by showing that the two extreme leverage deviation groups are dominated by firms with weak governance. The author also shows that the rebalancing speed is faster for firms with strong governance systems.

The paper proposes that a firm characterized by a strong governance system will display a shorter-duration deviation from the target capital structure and a higher adjustment level than a firm with weak governance. In other words, the author argues that the deviation from the target capital structure and the adjustment level are related to the quality of corporate governance. The results indicate that firms with a stronger governance structure are characterized by shorter-term deviations from the target. The author also finds that firms belonging to the two subsamples where leverage deviation is at extremely high or low levels are characterized by a weak governance system. The results corroborate the hypothesis on the speed of adjustment toward the desired target leverage. Furthermore, the author empirically proves that the adjustment level of firms with stronger governance is higher in both extreme leverage situations. This paper extends the existing literature on capital structure adjustment by introducing the effect of corporate governance.

This article aims to discuss the binary matrix of spatial association which is suggested by Moran, and proposes a new method of the definition of the w matrix to obtain a new space‐time correlation coefficient considering the correlation of both time and space.

From the perspective of the multi‐dimension of space and time, this article proposes a new computational method of a correlation coefficient considering both temporal and spatial factors, based on the analysis of the characteristics of Moran's Global Index and Moran's Local Index. The number of patents granted in mainland China's provinces and municipalities is taken as an example of multi‐dimensional analysis.

The results of quantitative analysis using this space‐time correlation coefficient show that the outcomes calculated by this new correlation coefficient are not only highly correlated with Moran's Index, but also have advantages in analyzing the trends of both spatial and temporal indicators simultaneously, which is verified by the illustration of the algorithm.

Due to a scarcity of data in China, the algorithm is based on data for the last 20 years, which may not be long enough for this research. Although this does not reduce the value of the conclusions of this article, a closer look should be taken at the effectiveness of the new space‐time correlation coefficient in the future.

The results of space‐time correlation coefficient are highly correlated with Moran's Index. In addition, it can not only analyze the “flow” indicators in a certain period but also analyze the “stock” indicators to reflect both space and time changes. These may reflect superiority of space‐time correlation coefficient to Moran's Index.

This new correlation coefficient that considers both temporal and spatial factors and will provide a more scientific and effective tool for spatial econometric analysis in time and space changes of management on society and the economy.