Oxford Research Encyclopedia of Business and Management最新文献

{"title":"Japanese Department Stores","authors":"R. Fujioka","doi":"10.1093/acrefore/9780190224851.013.95","DOIUrl":"https://doi.org/10.1093/acrefore/9780190224851.013.95","url":null,"abstract":"Dry goods stores, the predecessors of Japanese department stores, were forced to modernize and change their business format after the Meiji Restoration in 1868, which led to the demise of their main customers. The largest dry goods store, Mitsukoshi, was the first to learn about modern retailing in the West, and it broke out of the mold of the traditional Japanese retailer in around 1900 in an effort to catch up with Western department stores. Other large dry goods stores were quick to follow its lead: they transformed into department stores and created their own “cathedrals of consumption” in the 1920s, to match those in the West. This new retail format strongly contributed to Japan’s economic growth and to the Westernization of the Japanese lifestyle.\u0000 Despite numerous publications on the history of department stores, there has been little research on this transfer of Western department stores into a very different world: Japan. Although there are many studies on Japanese department stores in Japanese, focusing on how they were influenced by Western department stores, they are mostly subdivided on the basis of specific topics, such as levels of consumption in the interwar period or their economic impact during Japan’s period of high economic growth. The focus here is on the whole development process of department stores, bridging the gap between Western and Japanese studies on department stores.\u0000 The first stage in the development of Japanese department stores was in the early 20th century, when Japanese retailers raced to catch up with Western department stores to become modern Western-style retailers themselves; the second stage was in the late 20th century, when these new Japanese stores continued developing along their own unique path in order to target the domestic market during the growth of the Japanese economy, introducing ready-to-wear clothing, luxury brands, and gift products. In this way, Japanese department stores succeeded in increasing their efficiency and establishing a more upmarket image. However, in exchange for this prosperity, department stores also gave up control of their sales floors to the wholesalers and reduced their own merchandising skills. After the economic bubble burst in 1991, Japanese department stores began to suffer from decreased sales and lack of control over the points of sale in their stores.","PeriodicalId":294617,"journal":{"name":"Oxford Research Encyclopedia of Business and Management","volume":"95 32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129199901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Career Development and Organizational Support","authors":"M. Coetzee","doi":"10.1093/acrefore/9780190224851.013.168","DOIUrl":"https://doi.org/10.1093/acrefore/9780190224851.013.168","url":null,"abstract":"The complexity of modern careers requires personal agency in managing career development and employability capital as personal resources for career success. Individuals’ employability capital also serves as a valuable resource for the sustainable performance of organizations. Individuals’ ability to proactively engage in career self-management behaviors through the use of a comprehensive range of self-regulatory capabilities, known as career metacapacities, contributes to their employability capital. Organizational career development supports initiatives that consider individuals’ proactivity in light of conditions that influence their motivational states, and availability of personal resources helps organizations benefit from individuals who bring information, knowledge, capacities, and relationship networks (i.e., employability capital) into their work that ultimately contribute to the organization’s capability to sustain performance in uncertain, highly competitive business markets. Career development support practices should embrace the individualization of modern-day careers, the need for whole-life management, and the multiple meanings that career success has for individuals.","PeriodicalId":294617,"journal":{"name":"Oxford Research Encyclopedia of Business and Management","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117342708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intersectionality Theory and Practice","authors":"Doyin Atewologun","doi":"10.1093/ACREFORE/9780190224851.013.48","DOIUrl":"https://doi.org/10.1093/ACREFORE/9780190224851.013.48","url":null,"abstract":"Intersectionality is a critical framework that provides us with the mindset and language for examining interconnections and interdependencies between social categories and systems. Intersectionality is relevant for researchers and for practitioners because it enhances analytical sophistication and offers theoretical explanations of the ways in which heterogeneous members of specific groups (such as women) might experience the workplace differently depending on their ethnicity, sexual orientation, and/or class and other social locations. Sensitivity to such differences enhances insight into issues of social justice and inequality in organizations and other institutions, thus maximizing the chance of social change.\u0000 The concept of intersectional locations emerged from the racialized experiences of minority ethnic women in the United States. Intersectional thinking has gained increased prominence in business and management studies, particularly in critical organization studies. A predominant focus in this field is on individual subjectivities at intersectional locations (such as examining the occupational identities of minority ethnic women). This emphasis on individuals’ experiences and within-group differences has been described variously as “content specialization” or an “intracategorical approach.” An alternate focus in business and management studies is on highlighting systematic dynamics of power. This encompasses a focus on “systemic intersectionality” and an “intercategorical approach.” Here, scholars examine multiple between-group differences, charting shifting configurations of inequality along various dimensions.\u0000 As a critical theory, intersectionality conceptualizes knowledge as situated, contextual, relational, and reflective of political and economic power. Intersectionality tends to be associated with qualitative research methods due to the central role of giving voice, elicited through focus groups, narrative interviews, action research, and observations. Intersectionality is also utilized as a methodological tool for conducting qualitative research, such as by researchers adopting an intersectional reflexivity mindset. Intersectionality is also increasingly associated with quantitative and statistical methods, which contribute to intersectionality by helping us understand and interpret the individual, combined (additive or multiplicative) effects of various categories (privileged and disadvantaged) in a given context. Future considerations for intersectionality theory and practice include managing its broad applicability while attending to its sociopolitical and emancipatory aims, and theoretically advancing understanding of the simultaneous forces of privilege and penalty in the workplace.","PeriodicalId":294617,"journal":{"name":"Oxford Research Encyclopedia of Business and Management","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121737971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Inter-Firm and Intra-Firm Managerial Mobility","authors":"J. Broschak","doi":"10.1093/acrefore/9780190224851.013.88","DOIUrl":"https://doi.org/10.1093/acrefore/9780190224851.013.88","url":null,"abstract":"Inter- and intrafirm managerial mobility has emerged as a topic of growing interest among management and organizational scholars. The movement of managers within and between organizations is one of the fundamental processes that links organizations and labor markets and has been the focus of research in organizational behavior, strategy, organization theory, and entrepreneurship for more than 50 years. Managerial mobility affects career opportunities and labor market outcomes for individual managers; influences the structure, strategy, routines, and processes of organizations; and shapes the environments within which organizations operate. Thus, managerial mobility research is a key to unlocking our understanding of a wide range of organizational behaviors and outcomes at several different analytical levels.\u0000 Readers are introduced to the topic of managerial mobility and the vast body of existing research is summarized here. To help researchers understand the phenomenon, “managerial mobility” is distinguished from the more general topic of “employee mobility,” various terms that researchers have used to characterize managerial mobility processes are defined, and a distinction is made between intra- and interorganizational mobility. Next, because managerial mobility is a complex process, relevant research on the antecedents of managerial mobility is identified, categorizing some of the most important predictors into individual-, organizational-, and environmental-level antecedents. To demonstrate to researchers the importance of studying managerial mobility, some of the significant consequences of managerial mobility are highlighted, again distinguishing between consequences for individuals, organizations, and the environments in which they reside. To conclude, four potential directions for research to guide scholars and help set a research agenda on lines of inquiry on intra- and interorganizational managerial mobility are offered.","PeriodicalId":294617,"journal":{"name":"Oxford Research Encyclopedia of Business and Management","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127488795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect Size and Effect Uncertainty in Organizational Research Methods","authors":"S. Morris, Arash Shokri","doi":"10.1093/acrefore/9780190224851.013.238","DOIUrl":"https://doi.org/10.1093/acrefore/9780190224851.013.238","url":null,"abstract":"To understand and communicate research findings, it is important for researchers to consider two types of information provided by research results: the magnitude of the effect and the degree of uncertainty in the outcome. Statistical significance tests have long served as the mainstream method for statistical inferences. However, the widespread misinterpretation and misuse of significance tests has led critics to question their usefulness in evaluating research findings and to raise concerns about the far-reaching effects of this practice on scientific progress. An alternative approach involves reporting and interpreting measures of effect size along with confidence intervals. An effect size is an indicator of magnitude and direction of a statistical observation. Effect size statistics have been developed to represent a wide range of research questions, including indicators of the mean difference between groups, the relative odds of an event, or the degree of correlation among variables. Effect sizes play a key role in evaluating practical significance, conducting power analysis, and conducting meta-analysis. While effect sizes summarize the magnitude of an effect, the confidence intervals represent the degree of uncertainty in the result. By presenting a range of plausible alternate values that might have occurred due to sampling error, confidence intervals provide an intuitive indicator of how strongly researchers should rely on the results from a single study.","PeriodicalId":294617,"journal":{"name":"Oxford Research Encyclopedia of Business and Management","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128348701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Equality of Treatment, Opportunity, and Outcomes: Mapping the Law","authors":"Alain Klarsfeld, Gaelle Cachat-Rosset","doi":"10.1093/acrefore/9780190224851.013.315","DOIUrl":"https://doi.org/10.1093/acrefore/9780190224851.013.315","url":null,"abstract":"Equality is a concept open to many interpretations in the legal domain, with equality as equal treatment dominating the scene in the bureaucratic nation-state. But there are many possibilities offered by legal instruments to go beyond strict equality of treatment, in order to ensure equality of opportunity (a somehow nebulous concept) and equality of outcomes. Legislation can be sorted along a continuum, from the most discriminatory ones (“negative discrimination laws”) such as laws that prescribe prison sentences for people accused of being in same-sex relationships, to the most protective ones, labeled as “mandated outcome laws” (i.e., laws that prescribe quotas for designated groups) through “legal vacuum” (when laws neither discriminate nor protect), “restricted equal treatment” (when data collection by employers to monitor progress is forbidden or restricted), “equal treatment” (treating everyone the same with no consideration for outcomes), “encouraged progress” (when data collection to monitor progress on specific outcomes is mandatory for employers), and mandated progress (when goals have to be fixed and reached within a defined time frame on specified outcomes). Specific countries’ national legislation testify that some countries moved gradually along the continuum by introducing laws of increasing mandate, while (a few) others introduced outcome mandates directly and early on, as part of their core legal foundations. The public sector tends to be more protective than the private sector. A major hurdle in most countries is the enforcement of equality laws, mostly relying on individuals initiating litigation.","PeriodicalId":294617,"journal":{"name":"Oxford Research Encyclopedia of Business and Management","volume":"188 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132431937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Entrepreneurial Resilience","authors":"Roberta Garrett, Lauren Zettel","doi":"10.1093/acrefore/9780190224851.013.314","DOIUrl":"https://doi.org/10.1093/acrefore/9780190224851.013.314","url":null,"abstract":"Given that entrepreneurs regularly face challenges in the process of starting a new venture, their ability to adapt and respond to adversity is of great interest to entrepreneurship researchers. Hence, entrepreneurship scholars have begun to build on and extend the idea of individual-level, psychological resilience in the domain of entrepreneurship. Entrepreneurial resilience includes the processes entrepreneurs utilize to develop and deploy their capabilities in order to adapt and respond to adversity encountered in their role as an entrepreneur. Entrepreneurial resilience may be conceptualized as a set of capabilities, as a process, and as an outcome. The idea of entrepreneurial resilience as a set of capabilities implies that resilience is comprised of certain psychological and behavioral capacities or tendencies that allow an entrepreneur to overcome adversity. Entrepreneurial resilience as a process is the demonstration of those capabilities in action and is exhibited as entrepreneurs encounter and then recover from a stressor. Finally, entrepreneurial resilience as an outcome is often conceptualized as a lack of negative outcomes from an adverse or stressful event.\u0000 Research in entrepreneurship has begun to explore each of these conceptualizations of resilience. Importantly, resilience capabilities have been connected with a greater likelihood of venture survival. Additionally, research has demonstrated that entrepreneurial action may be an important tool that individuals use to overcome persistent adversity. Future research is needed to clarify how entrepreneurs both develop and deploy their capabilities and resources to achieve positive outcomes in the face of challenges. The remaining questions related to the nature of entrepreneurial resilience make this domain a promising field for continuing scholarship.","PeriodicalId":294617,"journal":{"name":"Oxford Research Encyclopedia of Business and Management","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131910512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Structural Equation Modelling","authors":"Wayne H. Crawford, Esther Lamarre Jean","doi":"10.1093/acrefore/9780190224851.013.232","DOIUrl":"https://doi.org/10.1093/acrefore/9780190224851.013.232","url":null,"abstract":"Structural equation modelling (SEM) is a family of models where multivariate techniques are used to examine simultaneously complex relationships among variables. The goal of SEM is to evaluate the extent to which proposed relationships reflect the actual pattern of relationships present in the data. SEM users employ specialized software to develop a model, which then generates a model-implied covariance matrix. The model-implied covariance matrix is based on the user-defined theoretical model and represents the user’s beliefs about relationships among the variables. Guided by the user’s predefined constraints, SEM software employs a combination of factor analysis and regression to generate a set of parameters (often through maximum likelihood [ML] estimation) to create the model-implied covariance matrix, which represents the relationships between variables included in the model. Structural equation modelling capitalizes on the benefits of both factor analysis and path analytic techniques to address complex research questions. Structural equation modelling consists of six basic steps: model specification; identification; estimation; evaluation of model fit; model modification; and reporting of results.\u0000 Conducting SEM analyses requires certain data considerations as data-related problems are often the reason for software failures. These considerations include sample size, data screening for multivariate normality, examining outliers and multicollinearity, and assessing missing data. Furthermore, three notable issues SEM users might encounter include common method variance, subjectivity and transparency, and alternative model testing. First, analyzing common method variance includes recognition of three types of variance: common variance (variance shared with the factor); specific variance (reliable variance not explained by common factors); and error variance (unreliable and inexplicable variation in the variable). Second, SEM still lacks clear guidelines for the modelling process which threatens replicability. Decisions are often subjective and based on the researcher’s preferences and knowledge of what is most appropriate for achieving the best overall model. Finally, reporting alternatives to the hypothesized model is another issue that SEM users should consider when analyzing structural equation models. When testing a hypothesized model, SEM users should consider alternative (nested) models derived from constraining or eliminating one or more paths in the hypothesized model. Alternative models offer several benefits; however, they should be driven and supported by existing theory. It is important for the researcher to clearly report and provide findings on the alternative model(s) tested.\u0000 Common model-specific issues are often experienced by users of SEM. Heywood cases, nonidentification, and nonpositive definite matrices are among the most common issues. Heywood cases arise when negative variances or squared multiple correlations greater th","PeriodicalId":294617,"journal":{"name":"Oxford Research Encyclopedia of Business and Management","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123743481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Innovation and Business Models","authors":"Lorenzo Massa, Christopher L. Tucci","doi":"10.1093/ACREFORE/9780190224851.013.296","DOIUrl":"https://doi.org/10.1093/ACREFORE/9780190224851.013.296","url":null,"abstract":"Starting from the mid-1990s, business models have received increased attention from both academics and practitioners. At a general level, a business model refers to the core logic that a firm or other type of organization employs to achieve its goals. Thus, in general terms, the business model construct attempts to capture the way organizations “do business” or operate to create, deliver, and capture value. Business model innovation (BMI) constitutes a unique dimension of innovation, different from and complementary to other dimensions of innovation, such as product/service, process, or organizational innovation. This distinction is important in that different dimensions of innovation have different antecedents, different processes, and, eventually, different outcomes.\u0000 Business models have been the subject of extensive research, giving birth to several lines of inquiry. Among them, one line focuses on business models in relation to innovation. This is a vast, somewhat fragmented, and evolving line of inquiry. Despite this limitation, it is possible to recognize that, at the core, business models are relevant to innovation in at least two main ways. First, business models can act as vehicles for the diffusion of innovation by bridging inventions, innovative technologies, and ideas to (often distant) markets and application domains. Therefore, business models speak to the phenomenon of technology transfer from the point of view of academic entrepreneurship and of corporate innovation. Thus, an important role of the business model in relation to innovation is to support the diffusion and adoption of new technologies and scientific discoveries by bridging them with the realization of economic output in markets. This is a considerable endeavor that relies on a complex process entailing the search for, and recombination of, complementary knowledge and capabilities. Second, business models are a subject of innovation that can become a source of innovation in and of themselves. For example, offerings that reinvent value to the customer—as opposed to offerings that incrementally add value to existing offerings—often involve designing novel business models. Relatedly, BMI refers to both a process (i.e., the dynamics involved in innovating business models) as well as the output of that process.\u0000 In relation to BMI as a process, the literature has suggested distinguishing between business model reconfiguration (BMR; i.e., the reconfiguration of an existing business model), and business model design (BMD; i.e., the design of a new business model from scratch). This distinction allows us to identify three possible instances, namely general BMR in incumbent firms, BMD in incumbent firms, and BMD in newly formed organizations and startups. These are arguably different phenomena involving different processes as well as different moderators. BMR could be understood as an evolutionary process occurring because of changes in activities and adjustments within an exi","PeriodicalId":294617,"journal":{"name":"Oxford Research Encyclopedia of Business and Management","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128823903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Inferential Statistics","authors":"R. Wilcox","doi":"10.1093/acrefore/9780190224851.013.280","DOIUrl":"https://doi.org/10.1093/acrefore/9780190224851.013.280","url":null,"abstract":"Inferential statistical methods stem from the distinction between a sample and a population. A sample refers to the data at hand. For example, 100 adults may be asked which of two olive oils they prefer. Imagine that 60 say brand A. But of interest is the proportion of all adults who would prefer brand A if they could be asked. To what extent does 60% reflect the true proportion of adults who prefer brand A?\u0000 There are several components to inferential methods. They include assumptions about how to model the probabilities of all possible outcomes. Another is how to model outcomes of interest. Imagine, for example, that there is interest in understanding the overall satisfaction with a particular automobile given an individual’s age. One strategy is to assume that the typical response Y, given an individuals age, X, is given by Y=β0+β1X, where the slope, β1, and intercept, β0, are unknown constants, in which case a sample would be used to make inferences about their values. Assumptions are also made about how the data were obtained. Was this done in a manner for which random sampling can be assumed? There is even an issue related to the very notion of what is meant by probability. Let μ denote the population mean of Y. The frequentist approach views probabilities in terms of relative frequencies and μ is viewed as a fixed, unknown constant. In contrast, the Bayesian approach views μ as having some distribution that is specified by the investigator. For example, it may be assumed that μ has a normal distribution. The point is that the probabilities associated with μ are not based on the notion of relative frequencies and they are not based on the data at hand. Rather, the probabilities associated with μ stem from judgments made by the investigator.\u0000 Inferential methods can be classified into three types: distribution free, parametric, and non-parametric. The meaning of the term “non-parametric” depends on the situation as will be explained. The choice between parametric and non-parametric methods can be crucial for reasons that will be outlined. To complicate matters, the number of inferential methods has grown tremendously during the last 50 years. Even for goals that may seem relatively simple, such as comparing two independent groups of individuals, there are numerous methods that may be used. Expert guidance can be crucial in terms of understanding what inferences are reasonable in a given situation.","PeriodicalId":294617,"journal":{"name":"Oxford Research Encyclopedia of Business and Management","volume":"205 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132975271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}