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The purpose of this paper is to understand how business process configurations influence motivation among process participants.

An experiment was conducted in which business process rules complexity, work backlog, and case distribution method were manipulated. Participant motivation and its antecedents were measured using a survey.

The study finds that business process configurations influence the motivation of process participants through their effect on perceived competence. Increasing business process rules complexity reduces competence. The effect of case distribution method on competence depends on backlog. Sequential distribution undermines competence in the presence of backlog, and enhances competence when backlog is absent. However, batch distribution results in higher competence in the presence of backlog than in its absence.

The study confirms the applicability of self-determination theory for analyzing the effect of work settings, including business process configurations, on employee motivation. The study further demonstrates the applicability of the task technology fit model in the context of business process automation.

The study suggests that reducing process complexity through the use of information technology can benefit process participant motivation. Additionally, the study highlights the importance of case distribution method on performance expectations.

While much of the extant research has considered the enhancement of business processes at the organizational level, this study examines how business process design can be used to preserve and potentially enhance the motivation of human process participants.

The purpose of our study is to investigate how a manufacturing plant’s internal operations along with its network of connections (upstream and downstream) can have an impact on its recovery time from a disruption. The authors also examine the inverse-U impact of complexity. Finally, the authors test the moderating role that business continuity management plans (BCP) at the plant level have on recovery time.

To test our hypotheses, the authors partnered with Resilinc Corporation, a Silicon Valley-based provider of supply chain risk management solutions to identify focal firms’ suppliers, customers and plant-level data including information on parts, manufacturing activities, bill of materials, alternate sites and formal business continuity plans. The authors employed censored data regression technique (Tobit).

Several important findings reveal that the plant’s internal operations and network connections impact recovery time. Specifically, the number of parts manufactured at the plant as well as the number of internal plant processes significantly increase disruption recovery time. In addition, the number of supply chains (upstream and downstream) involving the plant as well as the echelon distance of the plant from its original equipment manufacturer significantly increase recovery time. The authors also find that there exists an inverted-U relationship between complexity and recovery time. Finally, the authors find partial support that BCP will have a negative moderating effect between complexity and recovery time.

This research highlights gaps in the literature related to supply chain disruption and recovery. There is a need for more accurate methods to measure recovery time, more research on recovery at the supply chain site level and further analysis of the impact of supply chain complexity on recovery time.

This study aims to draw the attention of business process management (BPM) research and practice to the textual data generated in the processes and the potential of meaningful insights extraction. The authors apply standard natural language processing (NLP) approaches to gain valuable knowledge in the form of business process (BP) complexity concept suggested in the study. It is built on the objective, subjective and meta-knowledge extracted from the BP textual data and encompassing semantics, syntax and stylistics. As a result, the authors aim to create awareness about cognitive, attention and reading efforts forming the textual data-based BP complexity. The concept serves as a basis for the development of various decision-support solutions for BP workers.

The starting point is an investigation of the complexity concept in the BPM literature to develop an understanding of the related complexity research and to put the textual data-based BP complexity in its context. Afterward, utilizing the linguistic foundations and the theory of situation awareness (SA), the concept is empirically developed and evaluated in a real-world application case using qualitative interview-based and quantitative data-based methods.

In the practical, real-world application, the authors confirmed that BP textual data could be used to predict BP complexity from the semantic, syntactic and stylistic viewpoints. The authors were able to prove the value of this knowledge about the BP complexity formed based on the (1) professional contextual experience of the BP worker enriched by the awareness of cognitive efforts required for BP execution (objective knowledge), (2) business emotions enriched by attention efforts (subjective knowledge) and (3) quality of the text, i.e. professionalism, expertise and stress level of the text author, enriched by reading efforts (meta-knowledge). In particular, the BP complexity concept has been applied to an industrial example of Information Technology Infrastructure Library (ITIL) change management (CHM) Information Technology (IT) ticket processing. The authors used IT ticket texts from two samples of 28,157 and 4,625 tickets as the basis for the analysis. The authors evaluated the concept with the help of manually labeled tickets and a rule-based approach using historical ticket execution data. Having a recommendation character, the results showed to be useful in creating awareness regarding cognitive, attention and reading efforts for ITIL CHM BP workers coordinating the IT ticket processing.

While aiming to draw attention to those valuable insights inherent in BP textual data, the authors propose an unconventional approach to BP complexity definition through the lens of textual data. Hereby, the authors address the challenges specified by BPM researchers, i.e. focus on semantics in the development of vocabularies and organization- and sector-specific adaptation of standard NLP techniques.

Public procurement activities have long been treated as a minor subset of industrial or business-to-business buying. Consequently, the literature reports sparse research on the nature of government buying or how commercial firms can successfully market to the government. While this lack of research may not have been critical with respect to traditional public buying, recent procurement reforms and new contracting arrangements suggest our knowledge of business-to-business buying is inadequate with respect to the new environment of public buying and government/business relationships. One important and unique issue is how to handle the relationship with business suppliers during the contract implementation process. This paper proposes a taxonomy of government/business relationships as an organizing framework for understanding the complexities of buyer-seller relationships in government contract implementation. Archival case studies provide illustrations and justification for the taxonomy.

The purpose of this paper is to present a business process measurement framework for the evaluation of a corpus of business processes modelled in different business process modelling approaches. The results of the application of the proposed measurement framework will serve as a basis for choosing business process modelling approaches.

The approach uses ideas of the goal question metric framework to define metrics for measuring a business process where the metrics answer the questions to achieve the goal. The weighted sum method (WSM) is used to aggregate the measure of attributes of a business process to derive an aggregate measure, and business process modelling approaches are compared based on the evaluation of business process models created in different business process modelling approaches using the aggregate measure.

The proposed measurement framework was applied to a corpus of business process models in different business process modelling approaches and is showed that insight is gained into the effect of business process modelling approach on the maintainability of a business process model. From the results, business process modelling approaches which imbibed the principle of separation of concerns of models, make use of reference or base model for a family of business process variants and promote the reuse of model elements performed highest when their models are evaluated with the proposed measurement framework. The results showed that the applications of the proposed framework proved to be useful for the selection of business process modelling approaches.

The novelty of this work is in the application of WSM to integrate metric of business process models and the evaluation of a corpus of business process models created in different business process modelling approaches using the aggregate measure.

Having complexity theory as the overarching conceptual rationale, this paper presents a research model that defines external drivers, strategic and internal business practices and performance outcomes in service firm contexts.

Using an original survey instrument, the authors empirically examine business process management (1) adopting the mediating roles of shared goal practices and technology imperative practices (2) involving moderating roles of competitive market environments and joint implementation practices.

In response to dynamic market complexity, firms implement business process management through shared goal practices and technology imperative practices for achieving customer service outcomes. The findings also suggest the moderating roles of competitive pressure and joint implementation practices.

Generalizations here are limited to service firms. Increasing customer service expectations (e.g. simplicity, convenience, visual images and rapid responses) require firms to involve cross-functional work throughout their organizational processes.

In digital environments, business process management requires socio-technological synergy through shared goal practices and technology imperative practices.

Building on a theory-driven research model, a survey instrument provides tools to examine business process management of service firms that sense dynamic market complexity challenges and translate them to achieve desirable customer service outcomes.

The purpose of this paper is to study the relationship between organizational adaptability, institutional leadership and business process reengineering performance using the tested complexity theory in a developing economy setting.

This study is correlation and cross-sectional and adopts institutional-level data collected via questionnaires from reengineered microfinance institutions in Uganda. Cluster analysis as data mining technique was used to classify cases based on respondents’ opinions into homogeneous clusters. Nvivo was used to understand the perceptions of business process reengineering performance based on qualitative data. The authors used structural equation modeling to derive the predictive model of business process reengineering performance in a developing world setting.

The authors find that organizational adaptability and institutional leadership are key predictors of business process reengineering performance. Results reveal a predictive model of 61 per cent based on structural equation modeling for the study variables. Cluster analysis as data mining approach explored complex patterns of reengineered business processes.

The use of cluster analysis is susceptible to problems associated with sampling error and absence of fit indices. However, the likelihood of these problems is reduced by the interaction with the data, practical implications and use of smart partial least square to generate structural equations based on derived measurement models of each study variable.

Policymakers of Bank of Uganda, Ministry of Finance and Economic Planning, should develop sound policies in relation to knowledge management, institutional leadership and adaptive mechanisms to enhance business process reengineering performance to take advantage of new knowledge opportunities for the improvement of their businesses.

Given the results from structural equations generated, managers need to consider institutional leadership and organizational adaptability as key drivers of business process reengineering performance in microfinance institutions. The results confirm the significant role of institutional leadership, organizational adaptability in determining business process reengineering performance outcomes.

Unlike most of the business process reengineering literature, this study contributes to literature by domesticating and testing complexity theory to explain business process reengineering performance in developing economies.

The purpose of this paper is to present business process point analysis (BPPA), a technique to measure business functional process size, based on function point analysis (FPA), and using business process model and notation (BPMN). This paper also discusses the assessment results of BPPA compared with FPA.

Two experimental studies with participants from academia and industry were conducted. The following aspects in the experimental studies were focused: similarity, application easiness, feasibility, and application benefits. The purpose of the experiment was to assess BPPA comparing with FPA as the BPPA design followed the FPA pattern.

Experimental results showed that both academia and industry groups highly rated similarity and application benefits for BPPA compared with FPA. However, only participants from industry highly rated BPPA for application easiness and feasibility. The results also showed that participants’ previous experiences did not influence their ratings on BPPA.

BPPA helps project managers to measure functional process size of business process management projects. As BPPA is derived from FPA, its mechanism is easily recognizable by project managers who are used to FPA. These results also show that both techniques are in most cases considered rather similar.

The role of big data and data analytics in the audit engagement process is evident. Notwithstanding, understanding how big data influences cognitive processes and, consequently, on the auditors’ judgment decision-making process is limited. The purpose of this paper is to present a conceptual framework on the cognitive process that may influence auditors’ judgment decision-making in the big data environment. The proposed framework predicts the relationships among data visualization integration, data processing modes, task complexity and auditors’ judgment decision-making.

The methodology to accomplish the conceptual framework is based on a thorough literature review that consists of theoretical discussions and comparative studies of other authors’ works and thinking. It also involves summarizing and interpreting previous contributions subjectively and narratively and extending the work in some fashion. Based on this approach, this paper formulates four propositions about data visualization integration, data processing modes, task complexity and auditors’ judgment decision-making. The proposed framework was built from cognitive theory addressing how auditors process data into useful information to make judgment decision-making.

The proposed framework expects that the cognitive process of data visualization integration and intuitive data processing mode will improve auditors’ judgment decision-making. This paper also contends that task complexity may influence the cognitive process of data visualization integration and processing modes because of the voluminous nature of data and the complexity of business processes. Hence, it is also expected that the relationships between data visualization integration and audit judgment decision-making and between processing mode and audit judgment decision-making will be moderated by task complexity.

There is a dearth of studies examining how big data and big data analytics affect auditors’ cognitive processes in making decisions. This paper will help researchers and auditors understand the behavioral consequences of data visualization integration and data processing mode in making judgment decision-making, given a certain level of task complexity.

With the advent of big data and the evolution of innovative audit procedures, the constructed framework can be used as a theoretical foundation for future empirical studies concerning auditors’ judgment decision-making. It highlights the potential of big data to transform the nature and practice of accounting and auditing.

This paper sets out to classify business process outsourcing (BPO), linking it to service level agreement (SLA) design needs.

The paper develops a framework based on prior literature to classify BPOs and illustrates it with field research of Indian vendors.

The paper identifies criticality and complexity as the dimensions of classification and explicates the role of SLAs along these dimensions.

This is an exploratory research involving four vendors. A larger study is needed to strengthen/enrich the proposed framework, and make the findings more conclusive.

The taxonomy aids BPO industry practitioners in understanding the characteristics of different processes and the control issues arising therein. It also helps analysts to make more qualified generalizations within the BPO industry.

The paper addresses a dearth of literature on BPOs, especially from a vendor perspective. The taxonomy serves to position future work in this fast‐growing field of research.