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This study aims to examine the association of technology acceptance variables with the intention of adopting e-government transformation, as defined by four dimensions, namely, using new technology systems, redesigning of governmental processes, restructuring of governmental organization and changing the organizational culture and behavior, from the perspective of city government employees in Indonesia and the Philippines.

Quantitative approach was used in the conduct of this research. Variables were operationalized into indicators, which were transmuted into a self-reported survey questionnaire. Survey data obtained from purposively sampled city government employees were analyzed using structural equation modeling.

Findings suggest that attitude is a pivotal predictor of intention to adopt e-government transformation across all four dimensions, while performance expectancy, social influence and facilitating conditions also positively influence the intention to adopt process redesign, organizational structuring and cultural and behavioral change in the city government. Respondents’ length of work experience appears as a significant moderating variable.

This study reports only on the findings from two cities in two countries, Surabaya in Indonesia and Davao in the Philippines. The determination of the sample size was done through purposive sampling, so the application of results should be done with prudence. The constructs used for the research model were chosen because of their prominence in the literature. This study made use of a simple linear regression model in hypothesizing the relationships of the constructs.

For e-government transformation to be adoptable and efficacious, supporting and facilitating conditions are necessary. Structural, technical and financial support, as well as legal framework, for local e-government transformation should be in place. Maintaining and sustaining the positive attitude toward it should be done.

Although many studies have been conducted on adoption of ICT-enabled government services from the citizens’ viewpoint, little has been done from the local government employees’ perspective, and no prior cross-country study has been made. This study fills those gaps in the e-government adoption literature. Further, this study has shown that technology acceptance variables’ roles as predictors of behavioral intention can be extended to other dimensions of e-government.

This paper aims to investigate the role that deep emotional feelings play in relation to process/service re-design and process/service improvement. It suggests that attention to these dimensions may be vital for successful and sustainable outcomes. It investigates whether these dimensions are accommodated within popular change methods such as the European business excellence model (EBEM) and the balanced scorecard (BS).

An emotional value (EMVAL) scale is tested and applied using survey methods on a large sample of staff engaged in change and improvement initiatives. For the purposes of comparison, two separate business units are selected; one unit following EBEM/BS methods; one unit following EMVAL.

The findings show that significant improvement in employee perceptions of successful outcomes occurs when applying EMVAL methods. There is also evidence of tangible performance improvement in the form of customer satisfaction, reduced cost, and efficiency gains.

The findings are significant for academics and practitioners concerned with quality improvement programmes, suggesting that emotional scaling methods can improve outcomes. An emotional scaling method is presented along with a methodology for implementation.

Whilst the role of understanding deeper emotions in customer relationships is becoming more prominent within the marketing literature, little research to date has explored quality and internal marketing aspects which this paper seeks to address.

The traditional methods for process modeling emphasize the process workflow considerations at the cost of the associated process structure and resource communication. In the real process world, however, all these aspects are integrated and appear simultaneously: the workflows are driven by communication across the structure of resources. The aim of this paper is to explore a new approach based on an innovative, two‐dimensional view of the process world in an enterprise, integrating the workflow, the structure, and the communication from the beginning on.

Contrary to the traditional methods, the workflow diagrams are not directly designed by the process modeler, but rather they are automatically generated from the connectivity of specified resource communication. The modular documentation contains text and graphic information about the entire process world (structure of process resources, structure of process workflows, resource communication and interaction, communication through internal/external interfaces).

A new systematic approach to modular, process‐oriented enterprise description has been developed. Its two‐dimensional model allows an integrated visualization of the entire process world. The resulting process documentation is absolutely consistent and of very high quality. The user‐friendly access to information is made possible by clear interdependencies of process‐defining objects embedded in a relational documentation model. An update of the complete documentation can be performed automatically from the common database. The successful software implementation of the prototype application and its use in small customer projects demonstrate the practical feasibility of the two‐dimensional approach.

The two‐dimensional process modeling (2DPM) is a new systematic approach to modular process‐oriented enterprise description. A software implementation based on the underlying model together with professional programming tools and principles would be necessary to arrive at a marketable product.

This chapter reports on a longitudinal quasi-experimental field study within an organizational design of a global consumer products manufacturer moving toward high-performance work systems (HPWSs) in North America by integrating business centers and self-directed work teams (SDWTs) coupled with 13 other action-levers within an integrated and bundled high-performance organizations (HPOs) re-design. The results of this organizational design effort are assessed using different types and levels of organizational outcomes (hard record data, behavioral, and attitudinal measures) along a 5-year temporal dimension punctuated by multiple time periods (baseline, during, and after). The organization, which was “built to change” (Lawler & Worley, 2006), in this research had already highly superior or “exemplar” (Collins, 2001) levels of organizational performance. Consequently, the real research question becomes: “What effect does state of the art organizational design and development have on an exemplar organization?” The study also calls into question the field's ability to truly assess exemplar organizations with existing measures of organizational change and development.

This conceptual paper presents a proposal for improving a performance measurement (PM) system implementation process based on enterprise engineering (EE) guidelines, which gives the process a sense of completeness.

This paper analyzes a well-known process for PM systems implementation organized in two phases: identifying, designing and implementing the top-level performance measures; and cascading the top-level measures and identify appropriate lower-level performance measures. The proposed improvements to the studied process derive from the EE guidelines, which establish a basis for the structure of an organizational management system, the formalization and synchronization of processes, performance expectations, exception handling and change management.

The study reveals that not all EE guidelines are covered by the analyzed process, with four of them having no evidence of being adopted: involvement of people in process design and implementation; ensuring interoperability between different systems in the information structure; addressing of all possible exceptions; coherence and consistency of semantics across all processes.

By the lens of EE guidelines, this paper advances a how-to-guide. This paper can support managers and researchers on PM system design and implementation, given the importance and relevance of EE recommendations having a consistent and well-structured procedure.

The food processing industry is growing with retail and catering supply chains. With the rising complexity of food products and the need to address food customization expectations, food processing systems are progressively shifting from production line to job-shops that are characterized by high flexibility and high complexity. A food job-shop system processes multiple items (i.e. raw ingredients, toppings, dressings) according to their working cycles in a typical resource and capacity constrained environment. Given the complexity of such systems, there are divergent goals of process cost optimization and of food quality and safety preservation. These goals deserve integration at both an operational and a strategic decisional perspective. The twofold purpose of this paper is to design a simulation model for food job-shop processing and to build understanding of the extant relationships between food flows and processing equipment through a real case study from the catering industry.

The authors designed a simulation tool enabling the analysis of food job-shop processing systems. A methodology based on discrete event simulation is developed to study the dynamics and behaviour of the processing systems according to an event-driven approach. The proposed conceptual model builds upon a comprehensive set of variables and key performance indicators (KPIs) that describe and measure the dynamics of the food job-shop according to a multi-disciplinary perspective.

This simulation identifies the job-shop bottlenecks and investigates the utilization of the working centres and product queuing through the system. This approach helps to characterize how costs are allocated in a flow-driven approach and identifies the trade-off between investments in equipment and operative costs.

The primary purpose of the proposed model relies on the definition of standard resources and operating patterns that can meet the behaviour of a wide variety of food processing equipment and tasks, thereby addressing the complexity of a food job-shop. The proposed methodology enables the integration of strategic and operative decisions between several company departments. The KPIs enable identification of the benchmark system, tracking the system performance via multi-scenario what-if simulations, and suggesting improvements through short-term (e.g. tasks scheduling, dispatching rules), mid-term (e.g. recipes review), or long-term (e.g. re-layout, working centres number) levers.

The purpose of this paper is to explore the possibility of using a metric to measure user acceptability of a system prior to its implementation.

Empirical research is carried within PISO^®, an existing process improvement method that harnesses the expertise of system users in redesigning systems. A metric called “warm glow” is trialled, designed to test the level of user acceptance to system change.

The paper finds that the “warm glow” metric was applied to a number of system redesigns applying the PISO method, to check user opinion of the existing system against the proposed system. It was found that use of the “warm glow” metric does give a measured approach to gauging acceptability. Two possible influences were considered during the study. The first was the Halo effect which suggests an optimal stage in the redesign at which to rate processes in terms of user opinion. Results in this case appeared consistent irrespective of time. The second was the Hawthorn effect which suggests that simply by being “singled out” to redesign the system, user opinions will be positively biased. Findings in this respect were inconclusive. The need is noted for further research into possible effects.

It is likely that such a technique could by used more widely than within the PISO method.

The paper provides a means of testing user acceptance to systems via rating of system processes.

Globally, healthcare managers continue to struggle with increasing demands for their services being delivered with limited or shrinking resources. It is, therefore, clear that systems, processes and practices need to change to meet these challenges. The purpose of this paper is to assess how integrating two improvement technologies, Lean and integrated care pathways (ICP) might help.

Lean and ICP in healthcare provide a platform to develop conceptual frameworks for integrating two approaches.

A conceptual integrated framework is provided to assist care pathway designers and implementers to consider the synergistic benefits of combining approaches to improvement.

The authors provide a conceptual framework that requires empirically testing.

This research provides a conceptual framework to aid practitioners to improve healthcare design and delivery.

For the first time, the authors bring together two approaches to improving patient care pathway design and consider how these are linked in relation to improving healthcare delivery.

AI-based robo-advisory (RA) represents a FinTech application that is already replacing retail investment advisors. In private banking (PB), clients also increasingly expect service provision across different digital channels, but with a higher degree of personalization. Hence, the present study investigates the impact of intelligent RA on the PB investment advisory process to derive both process (re)design knowledge and strategic guidance for artificial intelligence (AI) usage for PB investment advisory.

The present study applies an AI process impact analysis approach by decomposing AI-based RA into three AI application types: conversational agent, customer segmentation and predictive analytics. The analysis results along a reference PB investment advisory process reveal sub-process transformations which are applied for process redesign integrating AI.

The study results imply that AI systems (1) enable seamless client journeys, (2) increase advisor flexibility, (3) support the client–advisor relationship by applying an omnichannel approach and (4) demand advisor skills to be augmented with technical and statistical knowledge.

The research study contributes (1) an AI process impact analysis approach, (2) derives process (re)design knowledge for AI deployment and (3) develops strategic guidance for AI usage in PB investment advisory.

We all know that some organizations are more productive than others. We do not necessarily know why. The way in which the organization is structured is the basic determinant – it should offer a potential for high productivity which is realized in the way that work systems, processes and procedures are organized and the way in which the workforce is empowered and motivated. In this article I am assuming that an organization has undertaken a commitment to productivity improvement in its widest sense. This commitment (which unfortunately is all too rare), from the senior management team, has to be driven down into the organization through the organization structure and then implemented at all levels of the structure. So what kind of structure is best suited to delivering such productivity improvements? Before we examine the implications of specific structures we need to examine the concepts behind organizational structure and the reasons why changes may be necessary.