Understanding Employee Motivation and Organizational Performance: Arguments for a Set-Theoretic Approach

Empirical evidence demonstrates that motivated employees mean better organizational performance. The objective of this conceptual paper is to articulate the progress that has been made in understanding employee motivation and organizational performance, and to suggest how the theory concerning employee motivation and organizational performance may be advanced. We acknowledge the existing limitations of theory development and suggest an alternative research approach. Current motivation theory development is based on conventional quantitative analysis (e.g., multiple regression analysis, structural equation modeling). Since researchers are interested in context and understanding of this social phenomena holistically, they think in terms of combinations and configurations of a set of pertinent variables. We suggest that researchers take a set-theoretic approach to complement existing conventional quantitative analysis. To advance current thinking, we propose a set-theoretic approach to leverage employee motivation for organizational performance

Business Process Agility

Business processes are the central building blocks of how individuals, organizations, and industries participate with one another. In a dynamic environment, a firm’s ability to respond and adapt is dependent on the agility of its business processes. However, agility from a business process perspective has yet to be defined and measured. This paper refines the definition of operational agility from the IS literature and tests a conceptual model. A field study is used to evaluate a metric created for measuring business process agility and understanding the relationship between the firm’s system capabilities and management’s factors driving adoption of agile business processes

Business Process Maturity’s Effect on Performance

Recent adoption of the Business Process Maturity Model (BPMM) by the Object Management Group (OMG) provides a means for managers to benchmark and monitor business processes as well as a roadmap for process improvement. The expectation is that as maturity increases, the result is a positive impact on performance; however, little empirical research has examined to what extent, if any process maturity has on performance. We conduct a survey of manufacturing firms to study the effects of process maturity on performance for two boundary spanning processes: purchasing and order fulfillment. Our results indicate that organizations with more mature purchasing processes appear to have higher relative levels of efficiency process outcomes than those with less mature purchasing processes. Similarly more mature order fulfillment processes do appear to have higher relative levels of quality process outcomes than those with less mature order fulfillment processes

Lean Processes without Compromising Controls

In today’s economic environment, governments feel the pressure to operate more efficiently, and many are therefore considering the gradual and continuous process improvement that Lean provides. Lean begins by examining a process from beginning to end, without departmental barriers; identifying the parts of the process that are inefficient; making a case for Lean improvements; and improving the process by reducing activities and waste that don’t add value to the consumer of the process

Power imbalance between consumers and information aggregators

Analisa a necessidade de proteção da privacidade das informações nas relações de consumo. Aborda a responsabilização das organizações que coletam e agregam informações de consumidores na garantia da proteção dos dados e informações

A Feedback Control Approach to Maintain Consumer Information Load in Online Shopping Environments

The heterogeneity of e-commerce users requires online shopping environments to advance from a simple framework to one that is adaptive. This need results from the negative consequences of user frustration due to information load. We used a feedback control theory based approach to address the online consumer information overload issue in an adaptive manner. To demonstrate the efficacy of this feedback control approach, a design science method evaluated the feedback controller. The main effect was that the dynamic adaptivity did not have to rely on summarizing data for inference to the individual. The proposed feedback control design is therefore a robust and viable option for organizations to incorporate into their online shopping environments to accommodate user variation of information load for e-commerce adaptivity

AI-Enhanced Audit Inquiry: A Research Note

Artificial intelligence (AI) and machine learning (ML) are transforming organizations and will soon transform auditing. Many promising areas of AI and ML are within the continuous auditing context. However, the field has yet to recognize how AI and ML can be used for audit inquiry, an essential feature of both traditional audits and continuous auditing. In this research note, we discuss the potential viability of AI-enhanced audit inquiry using ‘‘bots’’ that automatically generate audit inquiries as well as evaluate client responses. In addition, we discuss opportunities for future research in this specific area of automated auditing

Ai-Enhanced Audit Inquiry: A Research Note

Artificial intelligence (AI) and machine learning (ML) are transforming organizations and will soon transform auditing. Many promising areas of AI and ML are within the continuous auditing context. However, the field has yet to recognize how AI and ML can be used for audit inquiry, an essential feature of both traditional audits and continuous auditing. In this research note, we discuss the potential viability of AI-enhanced audit inquiry using ‘‘bots’’ that automatically generate audit inquiries as well as evaluate client responses. In addition, we discuss opportunities for future research in this specific area of automated auditing

A Combinatorial Optimization Based Sample Identification Method for Group Comparisons

Researchers often face having to reconcile their sample selection method of survey with the costs of collecting the actual sample. An appropriate justification of a sampling strategy is central to ensuring valid, reliable, and generalizable research results. This paper presents a combinatorial optimization method for identification of sample locations. Such an approach is viable when researchers need to identify sites from which to draw a nonprobability sample when the research objective is for comparative purposes. Findings indicate that using a combinatorial optimization method minimizes the population variation assumptions based upon predetermined demographic variables within the context of the research interest. When identifying the location from which to draw a nonprobability sample, an important requirement is to draw from the most homogeneous populations as possible to control for extraneous factors. In comparison to a standard convenience sample with no identified location strategy, results indicate that the proposed combinatorial optimization method minimizes population variability and thus decreases the cost of sample collection