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This paper reviews existing business process (BP) modeling languages that are widely used in the industry as well as recent research work on modeling and analysis of BPs in the service-oriented environment and Internetware-based software paradigm. BPs in such environment are different from traditional BPs due to loose coupling of partner services, dynamic and on-the-fly selection of partners and run-time process adaptability. The unique characteristics of these BPs require formal modeling of the requirements and constraints in each phase of their life cycle, including design phase, implementation and deployment phase and execution phase.

The paper first provides a categorization of typical user requirements in each phase of the BP life cycle. Then a detailed comparison of the selected languages with respect to their requirement modeling and analysis capabilities in each of the identified categories is provided. The paper also discusses new requirements engineering research challenges arising from future software needs and emerging trends in software engineering in the context of Web-services-based BPs and Internetware.

There is a need to have a framework that provides support for user requirements modeling and analysis for all the phases of BP life cycle in an integrated manner. Such a framework would be useful not only in resolving the inconsistencies between requirements across phases but also in addressing the issues related to BP evolution due to changes in user requirements over time. Moreover, with the Internet of things (IoT) adoption in BPM, there is a need to have an integrated environment that provides support for capturing the resilience requirements of enterprise BPs as well as the mobility constraints of the underlying IoT devices.

This paper reviews existing BP modeling languages and frameworks and discusses the new requirements engineering research challenges arising from future software needs and the emerging trends in BP management in the service-oriented environment and Internetware-based software paradigm.

Pertinent information sharing across various government agencies, as well as non‐governmental and private organizations, is essential to assess the incident situation, identify the needed resources for emergency response and generate response plans. However, each agency may have incident management systems of its choice with valuable information in its own format, posing difficulty in effective information sharing. Application‐to‐application sharing cross agency boundaries will significantly reduce human efforts and delay in emergency response. Information sharing from disparate systems and organizations, however, requires solving of the interoperability issue. The purpose of this paper is to present the UICDS™‐based resource sharing framework as a step toward addressing the afore‐mentioned challenges.

A prototype middleware system is developed using a standards‐based information sharing infrastructure called UICDS™ (Unified Incident Command and Decision Support™), an initiative led by the Department of Homeland Security (DHS) Science and Technology division. This standards‐based middleware, resource management plug‐in utilizes the ontology of organizational structure, workflow activities and resources, and the inference rules to discover and share resource information and interoperability from different incident management applications.

The middleware prototype implementation shows that the UICDS™‐based interoperability between heterogeneous incident management applications is feasible. Specifically, the paper shows that the resource data stored in the Resource Directory Database (RDDB) of the NJ Office of Emergency Management (NJOEM), Hippocrates of the New Jersey Department of Health and Senior Services (NJDHSS) can be discovered and shared with other incident management systems using the ontology and inference rules.

This study illustrates the possible solutions to the application to application interoperability problem using the DHS initiated interoperability platform called UICDS™.

The resource discovery and emergency response planning can be automated using the incident domain ontology and inference rules to dynamically generate the location‐based incident response workflows.

This study examines which dimensions of a business environment are most important for attracting globally mobile self-initiated expatriates to a country. The authors use secondary data from the World Bank, the World Economic Forum, IMD and the World Population Review to test eight hypotheses involving six macro-contextual factors that prior studies suggest attract internationally mobile skilled professionals, such as self-initiated expatriates, to a country's business environment. The macro-contextual factors examined are socio-cultural, economic, natural, ecological, technological clusters and legal and regulatory.

The authors use secondary data from the World Bank, IMD, World Population Report and the World Economic Forum to test eight hypotheses concerning macro-contextual factors that attract self-initiated expatriates to a country's business environment.

The study finds that factors such as the ease of hiring foreign labor, the use of English, macroeconomic stability, the diversity of the workforce and the quality of life in a country positively influence the attractiveness of its business environment to self-initiated expatriates. The study also finds that a business environment's socio-cultural, natural, economic and legal and regulatory macro-contextual attributes make it attractive to self-initiated expatriates.

To reduce common source bias, the authors use secondary data from four sources to examine which of six macro-contextual factors make a sample of 63 national business environments attractive to self-initiated expatriates. This study is one of the few to examine the impact of business environments on global mobility.

The purpose of this study is to gain knowledge about Muslim consumer’s perceptions toward advertising practices.

The approach taken was qualitative methodology, using phenomenological method. The qualitative data through semi-structured interviews have been collected from 20 Muslim consumers, 9 participants were women and 11 were men. The interviews lasted between 45 and 60 min. Furthermore, documentation technique was used to cast further insight into the advertising practices and to corroborate other forms of evidence.

From Muslim consumer perceptions, this qualitative research has generated factors that may be considered in advertising practices. These factors consist of social values (family, tradition and culture), Islamic ethics and rules and regulations. In addition, several practices regarding advertising production were extracted to guide marketers when targeting Muslim consumers.

The generalizability of the findings was limited because of convenience sampling and the small sample size.

This study contributes to the knowledge in the field by exploring factors and practices that should be considered in advertising practices when targeting Muslim consumers.

The purpose of this study is to identify which social and psychological factors better determine intentions to quit smoking to inform public health policy.

Data for this cross-sectional study were collected via face-to-face interaction following the pen-and-paper method. A total of 371 usable responses were received from randomly selected respondents of eight public sector universities located in the South Punjab province of Pakistan. Partial least squares structural equation modeling analysis was performed using SmartPLS program. A supplementary qualitative study, based on 21 in-depth interviews with the smokers, was conducted to augment findings of the quantitative study.

Results showed that protection motivation theory and theory of planned behaviour are supported to predict intentions to quit smoking. Subjective norms have a greater influence on intentions to quit smoking than attitudes towards smoking cessation, while perceived behavioural control fails to predict intentions to quit smoking. Perceived rewards and perceived cost are significant in predicting attitudes towards smoking cessation, while extrinsic rewards predict intentions to quit smoking.

The existing models reported in the literature have sparsely investigated the cognitive (such as motivation and emotions) and social factors (such as social influence and behavioural controls) together as determinants of intentions to quit smoking, leaving room for more studies on an integrated model of these factors. This study takes the opportunity and proposes an integrated model encompassing psycho-social factors to predict tobacco consumption quitting behaviour in an emerging economy context.

Studies concentrating on digitalization and interconnected capabilities have increased over the past several decades. Digitalization capability and open innovation are perceived as sources of sustained competitiveness across disciplines. This study investigated how digitalization capability and coopetition strategy affect the sustainable performance of firms by exploring the role of internal and external factors in influencing the adoption and success of open innovation in emerging markets.

To test the hypothesis, the authors conducted a structural equation model analysis on 509 firm datasets from the hub cities in China, an innovative battlefield where multilateral cooperation and competition are interwoven for globalization, clean development and the enhancement of economic growth.

The authors found that a firm's digitalization capability positively impacts outbound/inbound open innovation, coopetition strategy and sustainable performance. This study’s results support a series of mediating effects through outbound/inbound open innovation and coopetition strategy. Also, it provides a nuanced understanding of how digitalization capability and open innovation can affect sustainable performance in emerging markets.

The present study provides a nuanced understanding of how digitalization capability and in/out-bound open innovation can affect sustainable performance in emerging markets. The authors believe this model contributes to current knowledge by filling several research gaps, and this study’s findings offer valuable and practical implications for achieving open innovation and creating sustainable performance.

The purpose of this paper is to show the development of an image processing-based portable equipment for an automatic wear debris analysis. It can analyze both the qualitative and quantitative features of machine wear debris: size, quantity, size distribution, shape, surface texture and material composition via color.

It comprises hardware and software components which can take debris in near real-time from a machine oil sump and process it for features diagnosis. This processing provides the information of the basic features on the user screen which can further be used for machine component health diagnosis.

The developed system has the capacity to replace the existing off-line methods due to its cost effectiveness and simplicity in operation. The system is able to analyze debris basic quantitative and qualitative features greater than 50 micron and less than 300 micron.

Wear debris basic features analysis tool is developed and discussed. The portable and near real-time analysis offered by the discussed work can be more technically effective as compared to the existing off-line and online techniques.

With multiple-related organizations, worldwide infections, deep economic recession and public disorder, and large consumption amount of anti-epidemic resources, the coronavirus disease 2019 (COVID-19) has been defined as a public health emergency of international concern (PHEIC). Nowadays, Wuhan has recovered from the pandemic disaster and reentered normalization. The purposes of this study are to (1) summarize organization collaboration patterns, successful experience and latent defects under across-stage evolution of Wuhan's cooperation governance mode against the pandemic, and on the basis, (2) reveal how the COVID-19 development trends and organizations' collaborative behaviors affected each other.

Detailed content analysis of online news reports covering COVID-19 prevention and control measures on the website of Wuhan Municipal Government was adopted to identify organizations and their mutual collaborative interrelationships. Four complex network (CN) models of organization collaboration representing the outbreak, preliminary control, recession and normalization stages, respectively, were established then. Time-span-based dynamic parameter analyses of the proposed networks, comprising network cohesiveness analysis and node centrality analysis, were undertaken to indicate changes of global and local characteristics in networks.

First, the definite collaborative status of Wuhan Headquarters for Pandemic Prevention and Control (WHPPC) has persisted throughout the period. Medical institutions and some other administrations were the most crucial participants collaborating with the WHPPC. Construction-industry organizations altered pandemic development trends twice to make the situation controllable. Media, large-scale enterprises, etc. set about underscoring themselves contributions since the third stage. Grassroots cadres and healthcare force, small and medium-sized enterprises (SMEs), financial institutions, etc. were essential collaborated objects. Second, four evolution mechanisms of organization collaboration responding to the COVID-19 in Wuhan has been proposed.

First, universality of Wuhan-style governance experience may be affected. Second, the stage-dividing process may not be the most appropriate. Then, data source was single and link characteristics were not considered when modeling.

This study may offer beneficial action guidelines to governmental agencies, the society force, media, construction-industry organizations and the market in other countries or regions suffering from COVID-19. Other organizations involved could also learn from the concluded organizations' contributions and four evolution mechanisms to find improvement directions.

This study adds to the current theoretical knowledge body by verifying the feasibility and effectiveness of investigating cooperation governance in public emergencies from the perspectives of analyzing the across-stage organization collaboration CNs.

The purpose of this study is to investigate the entropy generation in different nanofluids flow over a vertically moving rotating disk. Unlike the classical Karman flow, water-based nanofluids have various suspended nanoparticles, namely, Cu, Ag, Al₂O₃ and TiO₂, and the disk is also moving vertically with time-dependent velocity.

The Keller box technique numerically solves the governing equations after reduction by suitable similarity transformations. The shear stress and heat transport features, along with flow and temperature fields, are numerically computed for different concentrations of the nanoparticles.

This study is done comparatively in between different nanofluids and for the cases of vertical movement of the disk. It is found that heat transfer characteristics rely not only on considered nanofluid but also on disk movement. Moreover, the upward movement of the disk diminishes the heat-transfer characteristics of the fluid for considered nanoparticles. In addition, for the same group of nanoparticles, an entropy generation study is also performed, and an increasing trend is found for all nanoparticles, with alumina nanoparticles dominating the others.

This research is a novel work on a vertically moving rotating surface for the water-conveying nanoparticle fluid flow with entropy generation analysis. The results were found to be in good agreement in the case of pure fluid.

The purpose of this paper is to review previous research studies on mathematical models for entropy generation in the magnetohydrodynamics (MHD) flow of nanofluids. In addition, the influence of various parameters on the velocity profiles, temperature profiles and entropy generation was studied. Furthermore, the numerical methods used to solve the model equations were summarized. The underlying purpose was to understand the research gap and develop a research agenda.

This paper reviews 141 journal articles published between 2010 and 2022 on topics related to mathematical models used to assess the impacts of various parameters on the entropy generation, heat transfer and velocity of the MHD flow of nanofluids.

This review clarifies the application of entropy generation mathematical models, identifies areas for future research and provides necessary information for future research in the development of efficient thermodynamic systems. It is hoped that this review paper can provide a basis for further research on the irreversibility of nanofluids flowing through different channels in the development of efficient thermodynamic systems.

Entropy generation analysis and minimization constitute effective approaches for improving the performance of thermodynamic systems. A comprehensive review of the effects of various parameters on entropy generation was performed in this study.