Search results

In organizational research the object of study is often a process, that is, a complex of events and activities that unfolds over time. In this chapter we focus on temporally ordered configurations, which can be defined as those configurations in which conditions occur in a specific temporal order. We illustrate the aims, characteristics, and limitations of several approaches that have been proposed as tools for the analysis of temporal order. Our illustration involves an analysis of the “gestation activities” of nascent entrepreneurs, that is, persons involved in the creation of a new firm. We aim to identify temporal sequences of gestation activities that generate or allow a successful outcome of the gestation process, while an occurrence of the same activities in another temporal order will not generate or allow that outcome. First we discuss Event Structure Analysis and Optimal Matching and conclude that these approaches cannot provide the kind of analysis that we are aiming at in this chapter. Then we discuss Temporal Qualitative Comparative Analysis, for which our analysis points to technical limitations that constrain its application. We then present and discuss an alternative approach, Temporal Necessary Condition Analysis.

This paper aims to describe two Web-based technologies of geographic information systems (GIS) to be used in monitoring and analysis of environmental processes, proposed by the authors. The technologies analyze the temporal aspect of the process together with the spatial aspect, which defers them from most other works on environmental processes, as these are usually limited either to spatial statistics or to temporal statistics. The approach is instrumental in dynamically finding the relationships between the processes and predicting critical incidents.

Often, the study of natural processes is limited to the analysis of their spatial properties presented by individual time series. The principal idea of this approach consists in supplementing this traditional analysis with the analysis of time fields. In this way, the authors are able to analyze temporal and spatial properties of environmental processes together.

The paper presents two technologies which provide the analysis of spatial and temporal data obtained in natural environment monitoring. The discussed spatio-temporal data mining methods are shown to enable the research into environmental processes, and the solution of practical issues of critical situation forecasts.

The paper discussed Web-based GIS technologies for the analysis of the temporal aspect of the environmental process together with the spatial aspect. Application examples demonstrate the ability of this approach to find the relationships in dynamics of the processes and to predict critical incidents.

Although acknowledged as a principal dimension in the context of text mining, time has yet to be formally incorporated into the process of visually representing the relationships between keywords in a knowledge domain. This paper aims to develop and validate the feasibility of adding temporal knowledge to a concept map via pair-wise temporal analysis (PTA).

The paper presents a temporal trend detection algorithm – vector space model – designed to use objective quantitative pair-wise temporal operators to automatically detect co-occurring hot concepts. This PTA approach is demonstrated and validated without loss of generality for a spectrum of information technologies.

The rigorous validation study shows that the resulting temporal assessments are highly correlated with subjective assessments of experts (n = 136), exhibiting substantial reliability-of-agreement measures and average predictive validity above 85 per cent.

Using massive amounts of textual documents available on the Web to first generate a concept map and then add temporal knowledge, the contribution of this work is emphasized and magnified against the current growing attention to big data analytics.

This paper proposes a novel knowledge discovery method to improve a text-based concept map (i.e. semantic graph) via detection and representation of temporal relationships. The originality and value of the proposed method is highlighted in comparison to other knowledge discovery methods.

This study aims to examine the evolution of spatial–temporal patterns in China’s hotel industry from 1978 to 2018.

A database comprising over 140,000 hotels with more than 30 rooms was created. The exploratory spatial–temporal data analysis (ESTDA) method, based on space–time cube model, was used to explore and visualize the spatial–temporal pattern of hotels.

The Chinese hotel industry can be divided into two development stages, namely, a large hotel-dominant stage before 2000 and a small–medium-sized hotel-dominant stage after 2000. China’s prefecture-level cities were clustered into four tiers. The higher the tier, the earlier the city will initiate hotel development. The Chinese hotel industry has four continuous hotspots (the Yangtze River Delta, Pearl River Delta, Bohai Rim and Sichuan and Chongqing) and some temporary hotspots.

This study lacks quantitative investigation, which could show the underlying mechanism of the evolution of the Chinese hotel industry.

This study is the first to investigate China’s hotel evolution over 40 years by applying big data and the ESTDA method. The systematic and evolutionary exploration will enable hotel researchers to understand the spatial–temporal nature of hotel distribution better. Introducing the ESTDA method into tourism and hotel research also provides an additional tool to researchers. Hotel investors and operators, city and tourism planners and market regulators can learn from the evolution of location patterns to make better where and when decisions.

This paper presents a developed spatial-temporal analysis framework for the case of investigating the business performance of construction consultancy services (CCS) in China.

The spatial-temporal analysis is based on the data envelopment analysis (DEA) technique. The spatial analysis follows the DEA results under a contemporaneous benchmark technology and a virtual decision-making unit, consisting of ranking analysis, cluster analysis and variation analysis. The temporal analysis is reliant on the DEA results under a global benchmark technology and the time value of money, including trend analysis and driving force analysis containing pure technical and scale efficiency factors.

Three CCS types in China are investigated, including engineering survey and design, construction supervision and procurement agency. The performance rank order and cluster classifications are mainly related to economic development levels. Engineering survey and design demonstrates the best performance and higher imbalances; however, construction supervision and procurement agency illustrate lower performance and imbalances. Scale efficiency significantly promotes business performance, whereas pure technical efficiency plays an inconspicuous role.

The CCS promote technical efficiency by developing their service and innovation levels. The service of engineering survey and design registered in Beijing, Shanghai and Guangdong is recommended for entering the service market in China.

The spatial-temporal analysis framework was developed, which is generic and provides a pathway to measure, compare and assess performance comprehensively. The CCS business performance is firstly measured.

Investigating the day of week and hour of day temporal patterns of crime typically show that (late) nights and weekends are the prime time for criminal activity. Though instructive, mental-health-related calls for service are a significant component of police service to the community that have not been a part of this research. The purpose of this paper is to analyze calls for police service that relate to mental health, using intimate partner/domestic related calls for police service for context.

Approximately 20,000 mental health related and 20,000 intimate partner/domestic related calls for police service are analyzed. Intra-week and intra-day temporal patterns are analyzed using circular statistics.

Mental-health-related calls for police service have a distinct temporal pattern for both days of the week and hours of the day. Specifically, these calls for police service peak during the middle of the week and in the mid-afternoon.

This is the first analysis regarding the temporal patterns of police calls for service for mental health-related calls. The results have implications for police resourcing and scheduling, especially in the context of special teams for addressing mental health-related calls for police service.

This paper aims to introduce a systematic computing and analytical procedure that is applied to the co-author network to identify the temporal evolution and growth of research collaborations in the area of e-governance. The empirical analysis of the temporal co-author network can trace the emerging authors and knowledge bursts over time.

The study applied social network theory to trace the author collaboration patterns in the domain of e-governance. Analysis of the co-author network using micro and macro parameters was done to trace the temporal evolution of the author collaborations.

E-governance is a multi-disciplinary research domain split over streams of management, politics, information technology and electronics. Hence, research collaborations play a significant role in its advancement. The knowledge sharing between individual authors, institutions and groups through research collaborations, resulting in extensive sharing of data, equipment and research methods, has boosted research activities and development in e-governance. In this paper, the authors systematically analyse the current scenario of research collaborations in the area of e-governance using co-author network to estimate its impact on the advancement of the field. The authors also analysed the temporal evolution of the co-author networks, which show remarkable growth of research collaborations in the domain of e-governance from the year 2000.

The co-author network analysis is only a proxy measure for the analysis of research collaborations. The names of the authors and the university affiliations used in the article are as retrieved from the research repository of Scopus. The degree, citations and other parameters related with authors have scope only within the environment of the co-author network used in the analysis. The criteria used in the study is limited to the degree of research collaborations and the number of co-authored publications in the giant component of the co-author network.

Institutions, authors and governments can trace and select suitable topics and choose research groups of co-authors over the world for future research collaborations in e-governance. The knowledge about the emerging and most discussed topics gives an overview of the global research trends of e-governance.

The study identified the evolution of creative collaborations in e-governance in the global perspective. The methodology introduced here is helpful to detect the proficient and productive author collaborations and the spectrum of related e-governance research topics associated with them. As the author collaborations can be mapped to the institutional and country-level collaborations, the information is helpful for researchers, institutions and governments to establish the best collaborations in e-governance research based on the author proficiency, collaboration patterns and research topics as per the requirements.

The paper introduces a novel research methodology using temporal analysis of co-author network to identify the evolution of research patterns and the associated research topics.

The purpose of this paper is to identify, classify and analyse temporality in information systems development (ISD) literature.

The authors address the temporality and ISD research gap by using a framework – which classifies time into three categories: conceptions of time, mapping activities to time and actors relating to time. The authors conduct a systematic literature review which investigates time in ISD within the Senior Scholars' Basket, Information Technology & People (IT&P), and top two information systems conferences over the past 20 years. The search strategy resulted in 9,850 studies of which 47 were identified as primary papers.

The results reveal that ISD research is ill equipped for contemporary thinking around time. This systematic literature review (SLR) contributes to ISD by finding the following gaps in the literature: (1) clock time is dominant and all other types of time are under-researched; (2) contributions to mapping activities to time is lacking and existing studies focus on single ISD projects rather multiple complex ISD projects; (3) research on actors relating to time is lacking; (4) existing ISD studies which contribute to temporal characteristics are fragmented and lack integration with other categories of time and (5) ISD methodology papers lack contributions to temporal characteristics and fail to acknowledge and contribute to time as a multifaceted interrelated concept.

This work has developed the first SLR on temporality in ISD. This study provides a starting point for ISD researchers and ISD practitioners to test commonly held temporal assumptions of ISD researchers and practitioners.

WeChat is the largest acquaintance social networking platform in China, in which users can view and reshare web pages shared by friends. This paper aims to analyze the spatio-temporal dynamics of web pages diffused in WeChat and advice on commercials.

A large number of web pages diffused in WeChat are collected and exclusively divided into four categories according to their titles, including advertisements, news bulletins, holiday greetings and emotional essays. For each web page, an information cascade (tree structure) is constructed to describe the diffusion trace. Based on the categories, the spatio-temporal popularity is characterized; the topological, temporal and spatial properties are examined; and the spatio-temporal diffusion velocity is explored.

Through comparative analysis, different categories of pages show diversity. For spatio-temporal popularity, there is no significant difference in cascade size; holiday greetings usually last for a relatively short time on average; emotional essays are more likely to spread to more provinces. For topological, temporal and spatial characteristics, the diffusion process of advertisements is more likely to be broadcasting than other categories; news bulletins and holiday greetings have an obvious bursty; the number of viewing behavior decreases from east to west in general. For spatio-temporal diffusion velocity, emotional essays diffuse the fastest in topological and spatio-temporal dimensions.

These findings contribute to promoting products and providing support for data driven modeling of information diffusion and human activity in spatio-temporal dimensions.

This paper brings focus and attention to the aspect of time within health information behaviour. The purpose of this paper is to critically assess and present strengths and weaknesses of utilising the infodemiology approach and metrics as a novel way to examine temporal variations and patterns of online health information behaviour. The approach is shortly exemplified by presenting empirical evidence for temporal patterns of health information behaviour on different time-scales.

A short review of online health information behaviour is presented and methodological barriers to studying the temporal nature of this behaviour are emphasised. To exemplify how the infodemiology approach and metrics can be utilised to examine temporal patterns, and to test the hypothesis of existing rhythmicity of health information behaviour, a brief analysis of longitudinal data from a large discussion forum is analysed.

Clear evidence of robust temporal patterns and variations of online health information behaviour are shown. The paper highlights that focussing on time and the question of when people engage in health information behaviour can have significant consequences.

Studying temporal patterns and trends for health information behaviour can help in creating optimal interventions and health promotion campaigns at optimal times. This can be highly beneficial for positive health outcomes.

A new methodological approach to study online health information behaviour from a temporal perspective, a phenomenon that has previously been neglected, is presented. Providing evidence for rhythmicity can complement existing epidemiological data for a more holistic picture of health and diseases, and their behavioural aspects.