Search results

Most setup management techniques associated with electronic assembly operations focus on component similarity in grouping boards for batch processing. These process planning techniques often minimize setup times. On the contrary, grouping with respect to component geometry and frequency has been proved to further minimize assembly time. Thus, we propose the Placement Location Metric (PLM) algorithm to recognize and measure the similarity between printed circuit board (PCB) patterns. Grouping PCBs based on the geometric and frequency patterns of components in boards will form clusters of locations and, if these clusters are common between boards, similarity among layouts can be recognized. Hence, placement time will decrease if boards are grouped together with respect to the geometric similarity because the machine head will travel less. Given these notions, this study develops a new technique to group PCBs based on the essences of both component commonality and the PLM. The proposed pattern recognition method in conjunction with the Improved Group Setup (IGS) technique can be viewed as an extended enhancement to the existing Group Setup (GS) technique, which groups PCBs solely according to component similarity. Our analysis indicates that the IGS performs relatively well with respect to an array of existing setup management strategies. Experimental results also show that the IGS produces a better makespan than its counterparts over a low range of machine changeover times. These results are especially important to operations that need to manufacture quickly batches of relatively standardized products in moderate to larger volumes or in flexible cell environments. Moreover, the study provides justification to adopt different group management paradigms by electronic suppliers under a variety of processing conditions.

Internet + and Electronic Business in China is a comprehensive resource that provides insight and analysis into E-commerce in China and how it has revolutionized and continues to revolutionize business and society. Split into four distinct sections, the book first lays out the theoretical foundations and fundamental concepts of E-Business before moving on to look at internet+ innovation models and their applications in different industries such as agriculture, finance and commerce. The book then provides a comprehensive analysis of E-business platforms and their applications in China before finishing with four comprehensive case studies of major E-business projects, providing readers with successful examples of implementing E-Business entrepreneurship projects.

Internet + and Electronic Business in China is a comprehensive resource that provides insights and analysis into how E-commerce has revolutionized and continues to revolutionize business and society in China.

We investigate the dynamics of competitive repositioning of firms in the deregulated U.S. airline industry (1979–1995) in terms of a firm's target market, strategic posture, and resource endowment relative to other firms in the industry. We suggest that, despite strong inertia in competitive positions, the direction of repositioning responds to external and internal alignment considerations. For external alignment, we examined how firms changed their competitive positioning to mimic the positions of similar, successful firms, and to differentiate themselves when experiencing intense rivalry. For internal alignment, we examined how firms changed their position in each dimension to align with the other dimensions of positioning. This internal alignment led to convergent positioning moves for firms with similar resource endowments and strategic postures, and divergent moves for firms with similar target markets and strategic postures. The evidence suggests that repositioning moves in terms of target markets and resource endowments are more sensitive to external and internal alignment considerations, but that changes in strategic posture are subject to very high inertia and do not appear to respond well to alignment considerations.

The comparison between economic growth and the character of monetary policy is one of the most frequently studied issues in policymaking. However, the number of studies incorporating a dynamic time warping approach to analyse the similarity of macroeconomic variables is relatively small.

The study aims at assessing the mutual similarity among various variables representing the financial sector (including the monetary policy by the central bank) and the real sector (e.g. economic growth, industrial production, household consumption expenditure), as well as cross-similarity between both sectors.

The analysis is based on the dynamic time warping (DTW) method, which allows for capturing various dimensions of changes of considered variables. This method is almost non-existent in the literature to compare financial and economic time series. The application of this method constitutes the main area of value added of the research. The analysis includes five variables representing the financial sector and five from the real sector. The study covers four countries: Czechia, Hungary, Poland and Romania and the 2010–2022 period (quarterly data).

The results show that variables representing the financial sector, including those reflecting monetary policy, are weakly correlated with each other, whereas the variables representing the real economy have a solid mutual similarity. As regards individual variables, for example, GDP fluctuations show relatively substantial similarity to ROE fluctuations – especially in Czechia and Hungary. In the case of Hungary and Romania, CAR fluctuations are consistent with GDP fluctuations. In the case of Poland and Hungary, there is a relatively strong similarity between the economy's monetisation and economic growth. Comparing the individual countries, two clusters of countries can be identified. One cluster includes Poland and Czechia, while another covers Hungary and Romania.

Internet + and Electronic Business in China is a comprehensive resource that provides insight and analysis into E-commerce in China and how it has revolutionized and continues to revolutionize business and society. Split into four distinct sections, the book first lays out the theoretical foundations and fundamental concepts of E-Business before moving on to look at internet+ innovation models and their applications in different industries such as agriculture, finance and commerce. The book then provides a comprehensive analysis of E-business platforms and their applications in China before finishing with four comprehensive case studies of major E-business projects, providing readers with successful examples of implementing E-Business entrepreneurship projects.

Internet + and Electronic Business in China is a comprehensive resource that provides insights and analysis into how E-commerce has revolutionized and continues to revolutionize business and society in China.

Organizations create their environments by constructing interpretations and then acting on them as if they were true. This study examines the cognitive spatial boundaries that managers of Manhattan hotels impose on their competitive environment. We derive and estimate a model that specifies how the attributes of managers’ own hotels and potential rival hotels influence their categorization of competing and non-competing hotels. We show that similarity in geographic location, price, and size are central to managers’ beliefs about the identity of their competitors, but that the weights they assign to these dimensions when categorizing competitors diverge from their influence on competitive outcomes, and indicate an overemphasis on geographic proximity. Although such categorization is commonly conceived as a rational process based on the assessment of similarities and differences, we suggest that significant distortions can occur in the categorization process and examine empirically how factors including managers’ attribution errors, cognitive limitations, and (in)experience lead them to make type I and type II competitor categorization errors and to frame competitive environments that are incomplete, erroneous, or even superstitious. Our findings suggest that understanding inter-firm competition may require greater attention being given to the cognitive foundations of competition.

We investigate the effects of management-employee similarity on mistreated employees’ propensities to engage in legal and organizational claiming, to quit, and to not seek a remedy in ongoing employment relationships.

We test hypotheses generated by the similarity-attraction and similarity-betrayal paradigms using Tobit regression and data from vignette-based employee surveys.

Mistreated employees with same-sex supervisors are more likely to initiate legal claims and to quit than those with opposite-sex supervisors, but less likely to initiate legal claims and to quit when they have a same-race supervisor than when they have a different-race supervisor. The effects of management-employee similarity on mistreated employees’ remedy-seeking responses exhibit asymmetries by gender and by race. The presence of same-race supervisors or other managers appears to diminish the greater reluctance of nonwhite employees, compared to white employees, to use organizational claiming mechanisms.

We know of no prior published research that has investigated the determinants of employees’ propensities to engage in multiple forms of remedy seeking, as well as the propensity to not seek a remedy, in response to plausibly illegal mistreatment not involving dismissal.

This article explores the effect of technological similarity in acquisitions on invention quantity and quality. In doing so, we confirm previous findings in the literature suggesting that technological similarity exhibits an inverted U-shaped relationship with innovative output and a negative relationship with average invention quality. However, we identify the nature of the technology as an important moderating factor for both relationships. We distinguish between two types of technologies, complex and discrete, and suggest that at high levels of technological similarity, invention quantity and average quality increase more in complex technology industries as compared to discrete technology industries. These effects are attributed to innovation cumulativeness and the interdependencies developed between patent rights in complex technology settings. A study of acquisition and patenting activity in two industries over a sixteen-year period provides empirical support to our claims.

This chapter extends research on peer review by utilizing and assessing an emerging methodology: automated textual analysis. In a corpus of 38 papers successfully revised for publication in Administrative Science Quarterly, the authors found that measures based on exact wording (measured by plagiarism detection) and sentence similarity (measured by Word Mover’s Distance) performed well in capturing differences between original submissions and published papers. They identified the same overall pattern of revision that authors reported (intensive revision of Theory and Discussion sections, limited modification of Methods), and were strongly correlated with the turnover in references and hypotheses that occurred in the course of peer review. Automated textual analysis can usefully contribute to the study of manuscript change in peer review and other social scientific contexts, particularly as available textual corpora grow in size.

Purpose – As researchers need partners to collaborate with, this study aims to provide author recommendation for academic researchers for potential collaboration, conference planning, and compilation of scientific working groups with the help of social information. Hereby the chapter analyzes and compares different similarity metrics in information and computer science.

Methodology/approach – The study uses data from the multidiscipline information services Web of Science and Scopus as well as the social bookmarking service CiteULike to measure author similarity and recommend researchers to unique target researchers. The similarity approach is based on author co-citation, bibliographic coupling of authors and collaborative filtering methods. The developed clusters and graphs are then evaluated by these target researchers.

Findings – The analysis shows, for example, that different methods for social recommendation complement each other and that the researchers evaluated user- and tag-based data from a social bookmarking system positively.

Research limitations/implications – The present study, providing author recommendation for six target physicists, is supposed to be a starting point for further approaches on social academic author recommendation.

Practical implications – The chapter investigates in recommendation methods and similarity algorithm models as basis for an implementation of a social recommendation system for researchers in academics and knowledge-intensive organizations.

Originality/value of chapter – The comparison of different similarity measurements and the user evaluation provide new insights into the construction of social data mining and the investigation of personalized recommendation.