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The business operations of today's enterprises are heavily influenced by numerous of internal and external business events. With the Event Driven Architecture and particularly the Complex Event Processing (CEP), the technology required for identifying complex correlations in these large amounts of event data right after its appearance has already emerged. The resulting gain in operational transparency builds the foundation for (near) real-time reactions. This motivated extensive research activities especially in the field of Business Process Management (BPM), which essentially coined the term Event-Driven BPM (EDBPM). Now, several years after the advent of this new concept, the purpose of this paper is to shed light to the question: where are we now on our way towards a sophisticated adoption of the CEP technology within BPM?

The research methodology of this paper is a structured literature analysis. It basically follows the procedure proposed by vom Brocke et al. (2009). This verified five-step process – entitled “Reconstructing the giant” – allowed a rigorous study. As a result, various research clusters were derived, whose state-of-the-art exposed existing research gaps within EDBPM.

First of all, the paper provides a concise conceptual basis on different application possibilities of EDBPM. Afterwards, it synthesizes current research into six clusters and highlights most significant work within them. Finally, a research agenda is proposed to tackle existing research gaps to pave the way towards fully realizing the potentials of the paradigm.

So far, a comparable study of the current state-of-the-art within EDBPM is non-existent. The findings of this paper, e.g. the proposed research agenda, help scholars to focus their research efforts on specific aspects that need to be considered in order to advance the adoption of the CEP technology within BPM.

The objective of the work is to analyze the impact of the Internet of Things (IoT) concepts and associated technologies in the framework of organizations and the management of their processes and how event orientation, as well as the structure of said business processes, can play an important role in this new organizational model. The main contribution of this work is to present a conceptualization of the research, identify approaches and challenges that require further study, and as a result, a proposal for future research.

The methodology comprises a qualitative analysis using secondary data. The approach relies on searches of scientific papers conducted in well-known databases, identifying research work around the IoT and Industry 4.0 applied to business process management. Based on the identified papers, the authors selected the most relevant and the latest publications, and categorized their contributions and findings based on open and selective coding. In total, the analysis is based on 95 papers that were selected and analyzed in depth.

The results of this research allow analyzing and ordering the existing contributions around Industry 4.0 and its impact on current organizations. The proposed conceptualization was derived from the analysis of the state of the research and identifies four categories: (1) improvements caused by Industry 4.0 and its impact on inter-organizational relations, (2) new architectural models and infrastructure of remote resources, their movement from the cloud to the edge and its effect on business processes, (3) context-aware concepts brought to business process management (BPM) linked to unstructured business processes and (4) complex event processing as a possible means for business processes sensitive to IoT signals.

The construction of current software ecosystems is strongly affected by the variety of information sources that feed them, as well as their volume. In addition, business processes represent organizations internally and are challenged to transcend the limits of companies due to the mentioned changes in software ecosystems. Industry 4.0 in conjunction with BPM re-defines the business process management paradigm and leads them to acquire the dynamism and sensitivity to the context that they usually did not have, as well as force them to move toward distributed platforms.

This paper assesses the state of the art in Industry 4.0 and business process management. The area can be defined as the intersection of two bigger areas highly relevant for organizations; on the one hand, the management and execution of business processes; and on the other hand, new conceptual, technological and methodological challenges to information systems that have to become more sensitive to event processing and also have to consume a large volume of data permanently and ubiquitously.

The purpose of this paper is to show how to employ complex event processing (CEP) for the observation and management of business processes. It proposes a conceptual architecture of BPM event producer, processor, and consumer and describes technical implications for the application with standard software in a perfect order scenario.

The authors discuss business process analytics as the technological background. The capabilities of CEP in a BPM context are outlined an architecture design is proposed. A sophisticated proof‐of‐concept demonstrates its applicability.

The results overcome the separation and data latency issues of process controlling, monitoring, and simulation. Distinct analyses of past, present, and future blur into a holistic real‐time approach. The authors highlight the necessity for configurable event producer in BPM engines, process event support in CEP engines, a common process event format, connectors to visualizers, notifiers and return channels to the BPM engine.

Further research will thoroughly evaluate the approach in a variety of business settings. New concepts and standards for the architecture's building blocks will be needed to improve maintainability and operability.

Managers learn how CEP can yield insights into business processes' operations. The paper illustrates a path to overcome inflexibility, latency, and missing feedback mechanisms of current process modeling and control solutions. Software vendors might be interested in the conceptualization and the described needs for further development.

So far, there is no commercial CEP‐based BPM solution which facilitates a round trip from insight to action as outlines. As major software vendors have begun developing solutions (BPM/BPA solutions), this paper will stimulate a debate between research and practice on suitable design and technology.

This paper emphasizes that employee attributional processing is a vital element in understanding employee aggression in organizations. The purpose of this paper is to summarize attributional perspectives and integrate recent theoretical advances into a comprehensive model.

The paper achieved its objectives by reviewing and integrating research and theories on aggression, cognitive processing, and attribution processes to explain how employee aggression unfolds in the workplace. Propositions are suggested.

It was found that early conceptualizations proposing that employee attributions and attribution styles would play important and significant roles in predicting employee aggression were supported by recent research enabling theoretical advancements.

Over the last 15 years, research advances show how attributions influence employee aggression. This paper integrates recent theoretical advances with prior empirical evidence and provides a comprehensive model exhibiting how attributions influence aggression in the workplace.

As the number of web applications is increasing day by day web mining acts as an important tool to extract useful information from weblogs and analyse them according to the attributes and predict the usage of a website. The main aim of this paper is to inspect how process mining can be used to predict the web usability of hotel booking sites based on the number of users on each page, and the time of stay of each user. Through this paper, the authors analyse the web usability of a website through process mining by finding the web usability metrics. This work proposes an approach to finding the usage of a website using the attributes available in the weblog which predicts the actual footfall on a website.

PROM (Process Mining tool) is used for the analysis of the event log of a hotel booking site. In this work, authors have used a case study to apply the PROM (process mining tool) to pre-process the event log dataset for analysis to discover better-structured process maps than without pre-processing.

This article first provided an overview of process mining, then focused on web mining and later discussed process mining techniques. It also described different target languages: system nets (i.e. Petri nets with an initial and a final state), inductive miner and heuristic miner, graphs showing the change in behaviour of the dataset and predicting the outcome, that is the webpage having the maximum number of hits.

In this work, a case study has been used to apply the PROM (process mining tool) to pre-process the event log dataset for analysis to discover better-structured process maps than without pre-processing.

This paper aims to present a solution that enables organizations to monitor and analyse the performance of their business processes by means of Big Data technology. Business process improvement can drastically influence in the profit of corporations and helps them to remain viable. However, the use of traditional Business Intelligence systems is not sufficient to meet today ' s business needs. They normally are business domain-specific and have not been sufficiently process-aware to support the needs of process improvement-type activities, especially on large and complex supply chains, where it entails integrating, monitoring and analysing a vast amount of dispersed event logs, with no structure, and produced on a variety of heterogeneous environments. This paper tackles this variability by devising different Big-Data-based approaches that aim to gain visibility into process performance.

Authors present a cloud-based solution that leverages (BD) technology to provide essential insights into business process improvement. The proposed solution is aimed at measuring and improving overall business performance, especially in very large and complex cross-organisational business processes, where this type of visibility is hard to achieve across heterogeneous systems.

Three different (BD) approaches have been undertaken based on Hadoop and HBase. We introduced first, a map-reduce approach that it is suitable for batch processing and presents a very high scalability. Secondly, we have described an alternative solution by integrating the proposed system with Impala. This approach has significant improvements in respect with map reduce as it is focused on performing real-time queries over HBase. Finally, the use of secondary indexes has been also proposed with the aim of enabling immediate access to event instances for correlation in detriment of high duplication storage and synchronization issues. This approach has produced remarkable results in two real functional environments presented in the paper.

The value of the contribution relies on the comparison and integration of software packages towards an integrated solution that is aimed to be adopted by industry. Apart from that, in this paper, authors illustrate the deployment of the architecture in two different settings.

With the rapid development of social media, the occurrence and evolution of emergency events are often accompanied by massive users' expressions. The fine-grained analysis on users' expressions can provide accurate and reliable information for event processing. Hence, 2,003,814 expressions on a major malignant emergency event were mined from multiple dimensions in this paper.

This paper conducted finer-grained analysis on users' online expressions in an emergency event. Specifically, the authors firstly selected a major emergency event as the research object and collected the event-related user expressions that lasted nearly two years to describe the dynamic evolution trend of the event. Then, users' expression preferences were identified by detecting anomic expressions, classifying sentiment tendencies and extracting topics in expressions. Finally, the authors measured the explicit and implicit impacts of different expression preferences and obtained relations between the differential expression preferences.

Experimental results showed that users have both short- and long-term attention to emergency events. Their enthusiasm for discussing the event will be quickly dispelled and easily aroused. Meanwhile, most users prefer to make rational and normative expressions of events, and the expression topics are diversified. In addition, compared with anomic negative expressions, anomic expressions in positive sentiments are more common. In conclusion, the integration of multi-dimensional analysis results of users' expression preferences (including discussion heat, preference impacts and preference relations) is an effective means to support emergency event processing.

To the best of the authors' knowledge, it is the first research to conduct in-depth and fine-grained analysis of user expression in emergencies, so as to get in-detail and multi-dimensional characteristics of users' online expressions for supporting event processing.

Many brands claim they were born by coincidence, yet the effects and contingencies of this communication strategy are little understood by extant marketing research on unexpected events. This study aims to investigate how consumers react to brand communications portraying a coincidental vs planned origin.

This research presents five experimental studies embedding coincidental brand origins into different types of marketing communications (i.e. crowdfunding campaigns, visual ads and brand biographies).

This research finds that coincidental brand origins increase persuasion (measured as money pledged to a crowdfunding campaign, overall brand equity and purchase intention) but only for consumers high in need for cognition (NFC). This effect is mediated by processing enjoyment, as the intrinsic need for thinking that characterizes high NFC consumers is satisfied by the opportunity to process the coincidence. Further to process, the authors show that explicitly providing an explanation for the coincidence makes the effect disappear, as this deprives high-NFC consumers of the opportunity to autonomously engage in and enjoy the cognitive process.

Brand managers able to leverage coincidences in their storytelling efforts should target high-NFC consumers and should not provide an explanation for the coincidences.

This research advances the limited literature on how consumers react to coincidences in a marketing context, the understanding of how brand communication strategies persuade consumers through information processing and the NFC literature.

A major problem of operational control in the services industry is the integration of customers in the delivery process. The aim of this paper is to develop a method that allows service companies to evaluate the impact of customer integration on operational control in service processes.

The development of the proposed method follows a design science approach. Thus, the method is conceptualised on the basis of production, services and information systems research. A case study of loan processing in a bank serves to evaluate the applicability of the method.

As a result of this study, customer integration should be included into operational control following three steps: identification of the type of customer integration; quantification and characterisation of the impact of the integration; and identification of the appropriate mechanisms of operational control to deal with the customer integration better. The results of the case study show that customer integration has an impact on certain activities within a service process only but the results can be used to enhance operational control.

The method can be used by process managers of service companies to identify the impact of customer integration on operational control. Thus, decisions within operational control and consequently the overall productivity of a service process can be improved.

The paper delivers a new insight how customer integration and operational control can be linked in service processes. Thus, a theoretical gap in service operations literature is filled. Furthermore, the case study demonstrates how the method can be used in practice.

Drawing on sensemaking and emotion regulation research, the purpose of this paper is to reconceptualize core contributor withdrawal (CCW) in the context of online peer-production communities (OPPCs). To explain the underlying mechanisms that make core contributors withdraw from these communities, the authors propose a process theory of contributor withdrawal called the core contributor withdrawal theory (CCWT).

To support CCWT, a typology of unmet expectations of online communities is presented, which uncovers the cognitive and emotional processing involved. To illustrate the efficacy of CCWT, a case study of the English version of Wikipedia is provided as a representative OPPC.

CCWT identifies sensemaking and emotion regulation concerning contributors’ unmet expectations as causes of CCW from OPPCs, which first lead to declined expectations, burnout and psychological withdrawal and thereby to behavioral withdrawal.

CCWT clearly identifies how and why important participation transitions, such as from core contributor to less active contributor or non-contributor, take place. By adopting process theories, CCWT provides a nuanced explanation of the cognitive and affective events that take place before core contributors withdraw from OPPCs.

CCWT highlights the challenge of online communities shifting from recruiting new contributors to preventing loss of existing contributors in the maturity stage. Additionally, by identifying the underlying cognitive and affective processes that core contributors experience in response to unexpected events, communities can develop safeguards to prevent or correct cognitions and emotions that lead to withdrawal.

CCWT provides a theoretical framework that accounts for the negative cognitions and affects that lead to core contributors’ withdrawal from online communities. It furthers the understanding of what motivates contributing to and what leads to withdrawal from OPPC.