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Workflow management includes concepts of special interest to the business organization field and for the automation of processes within a company. However, process modeling via workflow specifications and workflow management systems can be applied in any field where a workflow exists. The use of CASE tools provides a great increase in performance in information system development but, on the other hand, these tools do not support group work and make skipped steps possible in a methodology. Applying workflow management systems as a meta‐CASE tool together with the use of cooperative methodologies – that aim to capture user requirements – can help us to solve problems related to shortcomings in monitoring, controls, and audit information system development.

Scholarship on the state control of social movements has predominately focused on overt repression, resulting in comparatively less attention to more covert forms of control. Researchers have suggested that government surveillance of social movement organizations (SMOs) has become increasingly widespread and routinized in the post-September 11, 2001 era, but this hypothesis has remained untested. Since contemporary surveillance is grounded in a logic of information gathering that has diffused across law enforcement agencies since the September 11 attacks, government actors now cast a wide net and monitor a large variety of groups. This study shows that a result, traditional factors predicting surveillance, such as contentious behavior, have less explanatory power. Using a database of 409 SMOs active in Philadelphia between January 1996 and October 2009, the research asked who and why particular groups are monitored by the Pennsylvania Office of Homeland Security (PA-OHS) between November 2009 and September 2010. Bayesian logistic regression analysis is used to examine the variables predicting surveillance. Findings show that 23% of the SMOs in the sample were targets of surveillance. Organizational ideology was the strongest predictor and there was little evidence that history of contentious protests or previous conflict with the police influenced coming under surveillance. However, groups with less visibility in traditional media sources were more likely to be monitored.

This study aims to examine the moderating effects of gender, income, age, customer involvement and length of the relationship on the customer satisfaction (CS)‐customer loyalty (CL) relationship in a contractual service context. CL is assessed using customer repurchase intention (RI) and repurchase behavior (RB).

Using a postal mail survey, the authors measure the CS, RI involvement and socio‐demographic characteristics of customers who use a credit card. RB is measured by the number of transactions and the corresponding amount spent by clients, based on data provided by the company. The proposed hypotheses are tested using random sampling and hierarchical regressions.

The significant moderators are different depending on the CL measure used. When RI is utilized, the gender and age of the client have a positive effect on the CS‐CL relationship. However, when RB is assessed using the number of transactions made by the credit card's owner, the length of the relationship becomes the significant moderator.

The study is limited to a single firm, from one industry sector, but provides future researchers a multitude of replication opportunities.

Demographic and relational variables are important in explaining the CS‐CL relationship. Customer relationship strategies have positive results. RB is preferred to RI when evaluating and explaining CL.

The assessment of customer and relational characteristics as moderating variables in the CS‐CL relationship, and comparing different measures of CL in a contractual service adds value to this research.

Business Process Reengineering (BPR) eliminates non-value-added (NVA) and essential non-value-added (ENVA) waste through radical process redesign to improve organizational operations. Comprehensive research integrating BPR tools is needed to understand their benefits for manufacturing firms. This research presents an integrated BPR-simulation framework tailored to the manufacturing sector to maximize process improvements and operational excellence.

The BPR design methodology adopts a systematic, multi-stage approach. The first phase involves identifying a specific improvement process aligned with BPR's core objectives. This phase analyses and redesigns workflows to optimize task sequences, roles, and stakeholder interactions while eliminating redundancies and inefficiencies via Workflow Process Reengineering. Visual process mapping tools, including VSM and simulation, pinpoint areas of waste, delay, and potential enhancement. The second phase follows the workflow analysis and aims to improve efficiency and effectiveness by redefining roles, rearranging tasks, and integrating automation and technology solutions. The redesigned process undergoes evaluation against key performance indicators to ensure measurable improvements are achieved. The final phase validates the proposed changes through simulation models, assesses the impact on key performance metrics, and establishes the necessary infrastructure for successful implementation. The proposed model is empirically validated through a case study of a leading apparel company in Vietnam, confirming its effectiveness.

The findings reveal that NVA activities are being eliminated, and ENVA activities in key departments are significantly reduced. This yielded a substantial improvement, reducing 25 out of 186 combined ENVA and NVA operations in the sewing facility, involving a decrease of 15 ENVA operations and the removal of 10 NVA operations. Consequently, this led to an 8.5% reduction in the proportion of ENVA operations, accompanied by a complete 100% elimination of NVA activities.

The single case study limits generalizability; thus, expanded implementation across diverse manufacturing sub-sectors is required to establish validity and broader applicability of the integrated framework.

The experimental results highlight the proposed model's effectiveness in optimizing resource utilization and its practical implementation potential. This structured BPR methodology enables organizations to validate, evaluate, and establish proposed process changes to enhance operational performance and productivity.

In the Indian judicial system, the court considers interpretations of similar previous judgments for the present case. An essential requirement of legal practitioners is to determine the most relevant judgments from an enormous amount of judgments for preparing supportive, beneficial and favorable arguments against the opponent. It urges a strong demand to develop a Legal Document Recommendation System (LDRS) to automate the process. In existing works, traditionally preprocessed judgment corpus is processed by Doc2Vec to learn semantically rich judgment embedding space (i.e. vector space). Here, vectors of semantically relevant judgments are in close proximity, as Doc2Vec can effectively capture semantic meanings. The enormous amount of judgments produces a huge noisy corpus and vocabulary which possesses a significant challenge: traditional preprocessing cannot fully eliminate noisy data from the corpus and due to this, the Doc2Vec demands huge memory and time to learn the judgment embedding. It also adversely affects the recommendation performance in terms of correctness. This paper aims to develop an effective and efficient LDRS to support civilians and the legal fraternity.

To overcome previously mentioned challenges, this research proposes the LDRS that uses the proposed Generalized English and Indian Legal Dictionary (GEILD) which keeps the corpus of relevant dictionary words only and discards noisy elements. Accordingly, the proposed LDRS significantly reduces the corpus size, which can potentially improve the space and time efficiency of Doc2Vec.

The experimental results confirm that the proposed LDRS with GEILD yield superior performance in terms of accuracy, F1-Score, MCC-Score, with significant improvement in the space and time efficiency.

The proposed LDRS uses the customized domain-specific preprocessing and novel legal dictionary (i.e. GEILD) to precisely recommend the relevant judgments. The proposed LDRS can be incorporated with online legal search repositories/engines to enrich their functionality.

The Lattice Boltzmann (LB) method offers an alternative to conventional computational fluid dynamics (CFD) methods. However, its practical use for complex turbulent flows of engineering interest is still at an early stage. This paper aims to outline an LB wall-modeled large-eddy simulation (WMLES) solver.

The solver is dedicated to complex high-Reynolds flows in the context of WMLES. It relies on an improved LB scheme and can handle complex geometries on multi-resolution block structured grids.

Dynamic and acoustic characteristics of a turbulent airflow past a rod-airfoil tandem are examined to test the capabilities of this solver. Detailed direct comparisons are made with both experimental and numerical reference data.

This study allows assessing the potential of an LB approach for industrial CFD applications.

Are firms able to time the market? The purpose of this paper is to focus on the study of own stock trading, emphasizing both repurchase and resell operations on the open market as well as over the counter.

The authors use data on 37,997 own stock transactions from 2005 to 2015 of Euronext Lisbon listed firms. Following Dittmar and Field (2015), this paper uses relative transaction prices to ascertain the relative performance of own stock transactions, in the open market and over the counter.

Results show that firms can time both repurchases as well as resales. Firms repurchase (resell) at lower (higher) prices than those prevailing in the market. Moreover, market-timing ability proves to be higher after the bailout period and to be influenced by the own stock trading frequency. Trading on the open market allows for increased timing ability for own stock repurchasing and reselling activity. Finally, results show seasonal effects both in repurchase and resale performance. Also, more efficient but less valuable firms are more likely to be successful in timing the market.

The authors study both the repurchasing and the reselling activity of the same set of firms, of already issued stock, using high-frequency (daily) data. In addition, the authors study own stock trading both in the open market and OTC, and also study the impact of a major economic shift on the firms’ ability to time the market.

The purpose of this paper is to examine whether Real Estate Investment Trusts (REITs) returns on the different days of the week differ from each other.

It uses European Public Real Estate Association (EPRA)/National Association of Real Estate Investment Trusts (NAREIT) UK index daily closing values (GBP) and its two sub-indices FTSE EPRA/NAREIT UK REITs and non-REITs as dependent variables. It employs Kruskal-Wallis tests and dummy-variable regression to test the hypothesis.

The overall findings provide evidence that return anomalies exist in the UK REITs.

Thought significant, the absolute returns differences are modest for investors to gain superior returns in UK REITs. However, by recognising the day-of-the-week effect, investors can buy/sell UK REITs more effectively.

This research brings updated evidence of the contested calendar anomalies issues in REITs.

Destination management organizations perform a very important role regarding the management of tourism destinations. Destination management systems are a key technological infrastructure for these organizations. However, in the literature, it is not clear what are the factors that promote the implementation of these systems, neither what are the factors that contribute to their success. This study aims to propose and test two research models to overcome these research gaps.

The first model refers to the determinants of the implementation of destination management systems, and the second model refers to the determinants of the success of those systems. The models are tested with data collected through a questionnaire survey from destination management organizations of five European countries, which are among the leaders in international tourism receipts.

Concerning the factors that promote the implementation of destination management systems, this study reveals the importance of the diversity of partnerships that the private sector establishes in the destination, of advantages resulting from governance and of partners' involvement in the functions of destination management organizations. Concerning the factors that promote the success of these systems, this study highlights the importance of a phased implementation, the fact that a high number of functionalities in the system prevents success and the importance of having a revenue model that can support financial and operating costs.

The study provides important theoretical and practical contributions to the successful implementation of destination management systems by destination management organizations.

The purpose of this paper is to illustrate a business process modelling approach based on: the incorporation of the best practices in the industry; higher reliability standards for operation; real‐time settlement; improved security; and transparency in the process and information handling.

This novel process modelling considers three major phases. First, devising a new operating model covering the following main aspects: core services, secondary services, support services, common processes for all services and, system interaction with the national and international financial markets. Second, modelling of the redesigned business processes. Third, construction of a new system.

Significant improvements in the five attributes mentioned above were achieved by incorporating a straight‐through continuous processing model with a single entry and exit channel, a new account structure, an intelligent pre‐settlement process, and by stressing transparency in every process (system log).

The illustrated methodology represents close to 10,000 work‐hours of research and consultancy at the Mexican central securities depository –CSD (INDEVAL). Although, arithmetic results are case specific, insight knowledge can be easily adapted on other CSD worldwide.

International standards as well as the best international practices were incorporated in the new system. Hence, the operation of INDEVAL will be in the leading edge of financial systems.

The present contribution illustrates a comprehensive re‐design of a complex business environment. One of the most innovative proposals for this new model was the new pre‐settlement module which optimizes the settlement process. Moreover, the incorporation of a straight‐through continuous processing model for a securities depository provides a transparent and efficient operation for a CSD.