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Process orientation is important for improving organizational performance. The process view is considered a key enabler of digital transformation, and thus management control systems (MCS) are expected to incorporate this view. However, the existing body of knowledge is fragmented, as different process approaches are often considered independently following a reductionist view of control practices. This paper aims to provide recommendations for further research as well as guidance for practice by a systematic review of the state of research of MC for process orientation. It is based on both a comprehensive view to MC using an MCS package approach and a comprehensive view of process orientation.

A systematic literature review addressing major types of process orientation approaches was performed by applying the comprehensive MC framework of Malmi and Brown. The results were synthesized and propositions were developed.

All components of the MC framework, as well as MCS packages, are highly relevant for process orientation. Propositions regarding configurations of MC for process orientation show directions for future research. However, comprehensive considerations of packages and of individual components, especially cultural controls, remain scarce in the literature.

To the best of the authors‘ knowledge, this paper is the first of its kind to provide a comprehensive, structured overview of MC for process orientation, applying a nonreductionist view, based on an MCS Package approach, and consolidating the so far fragmented view of different process approaches.

Smart card-based E-payment systems are receiving increasing attention as the number of implementations is witnessed on the rise globally. Understanding of user adoption behavior of E-payment systems that employ smart card technology becomes a research area that is of particular value and interest to both IS researchers and professionals. However, research interest focuses mostly on why a smart card-based E-payment system results in a failure or how the system could have grown into a success. This signals the fact that researchers have not had much opportunity to critically review a smart card-based E-payment system that has gained wide support and overcome the hurdle of critical mass adoption. The Octopus in Hong Kong has provided a rare opportunity for investigating smart card-based E-payment system because of its unprecedented success. This research seeks to thoroughly analyze the Octopus from technology adoption behavior perspectives.

Cultural impacts on adoption behavior are one of the key areas that this research posits to investigate. Since the present research is conducted in Hong Kong where a majority of population is Chinese ethnicity and yet is westernized in a number of aspects, assuming that users in Hong Kong are characterized by eastern or western culture is less useful. Explicit cultural characteristics at individual level are tapped into here instead of applying generalization of cultural beliefs to users to more accurately reflect cultural bias. In this vein, the technology acceptance model (TAM) is adapted, extended, and tested for its applicability cross-culturally in Hong Kong on the Octopus. Four cultural dimensions developed by Hofstede are included in this study, namely uncertainty avoidance, masculinity, individualism, and Confucian Dynamism (long-term orientation), to explore their influence on usage behavior through the mediation of perceived usefulness.

TAM is also integrated with the innovation diffusion theory (IDT) to borrow two constructs in relation to innovative characteristics, namely relative advantage and compatibility, in order to enhance the explanatory power of the proposed research model. Besides, the normative accountability of the research model is strengthened by embracing two social influences, namely subjective norm and image. As the last antecedent to perceived usefulness, prior experience serves to bring in the time variation factor to allow level of prior experience to exert both direct and moderating effects on perceived usefulness.

The resulting research model is analyzed by partial least squares (PLS)-based Structural Equation Modeling (SEM) approach. The research findings reveal that all cultural dimensions demonstrate direct effect on perceived usefulness though the influence of uncertainty avoidance is found marginally significant. Other constructs on innovative characteristics and social influences are validated to be significant as hypothesized. Prior experience does indeed significantly moderate the two influences that perceived usefulness receives from relative advantage and compatibility, respectively. The research model has demonstrated convincing explanatory power and so may be employed for further studies in other contexts. In particular, cultural effects play a key role in contributing to the uniqueness of the model, enabling it to be an effective tool to help critically understand increasingly internationalized IS system development and implementation efforts. This research also suggests several practical implications in view of the findings that could better inform managerial decisions for designing, implementing, or promoting smart card-based E-payment system.

Cities are becoming smarter and more optimized because of digital transformation, reducing costs, increasing safety, attracting investment, ensuring sustainability, and increasing viability. As a result of this optimization, they are becoming smart cities. Smart cities use the Internet of Things’ devices, such as connected sensors, lights, and smart meters, to improve infrastructure and design by gathering and analyzing real-time citizen data. In this research, different conceptions of smart cities and their interconnections with digital transformation are presented. Therefore, the purpose of this chapter is to analyze how digital transformation may help manage smart cities. As a result, a thorough and integrated evaluation of the SCOPUS database will be conducted in order to address the following questions: (1) What are smart cities? (2) What is digital transformation? (3) How does digital transformation help to manage smart cities? The results point out that technologies and digital abundance, which include artificial intelligence, blockchain, and Internet of Things, play a crucial role in managing a controlled and automated infrastructure in smart cities. These favor the development of suitable places to live, work, and have fun, with a better quality of life for everyone.

Business ethics provide a potent source of competitive advantage, placing increasing pressure on organizations to create and maintain an ethical workforce. Nonetheless, ethical breaches continue to permeate corporate life, suggesting that there is something missing from how we conceptualize and institutionalize organizational ethics. The current effort seeks to fill this void in two ways. First, we introduce an extended ethical framework premised on sensemaking in organizations. Within this framework, we suggest that multiple individual, organizational, and societal factors may differentially influence the ethical sensemaking process. Second, we contend that human resource management plays a central role in sustaining workplace ethics and explore the strategies through which human resource personnel can work to foster an ethical culture and spearhead ethics initiatives. Future research directions applicable to scholars in both the ethics and human resources domains are provided.

Purpose: Risk is a multifaceted concept, and its identification requires complex approaches that are often misunderstood. The consequence is that decisions are based on limited perception rather than the full value and meaning of what risk is, as a result, the way it is being tackled is incorrect. The individuals are often limited in their perceptions and ideas and do not embrace the full multifaceted nature of risk. Regulators and individuals want to follow norms and checklists or overuse models, simulations, and templates, thereby reducing responsibility for decision-making. At the same time, the wider use of technology and rules reduces the critical thinking of individuals. We advance the automation process by building robots that follow protocols and forget about the part of risk assessment that cannot be programed. Therefore, with this study, the objective of this study was to discover how people define risk, the influencing factors of risk perception and how they behave toward this perception. The authors also determine how the perception differed with age, gender, marital status, education level and region. The novelty of the research is related to individual risk perception during COVID-19, as this is a new and unknown phenomenon. Methodology: The research is based on the analysis of the self-administered purposely designed questionnaires we distributed across different social media platforms between February and June 2020 in Europe and in some cases was carried out as a interview over communication platforms such as “Skype,” “Zoom” and “Microsoft Teams.” The questionnaire was divided into four parts: Section 1 was designed to collect demographic information from the participants; Section 2 included risk definition statements obtained from literature and a preliminary discussion with peers; Section 3 included risk behavior statements; and Section 4 included statements on risk perception experiences. A five-point Likert Scale was provided, and participants were required to answer along a scale of “1” for “Strongly Agree” to “5” for “Strongly Disagree.” Participants also had the option to elaborate further and provide additional comments in an open-ended box provided at the end of the section. 466 valid responses were received. Thematic analysis was carried out to analyze the interviews and the open-ended questions, while the questionnaire responses were analyzed using various quantitative methods on IBM SPSS (version 23). Findings: The results of the analysis indicate that individuals evaluate the risk before making a decision and view risk as both a loss and opportunity. The study identifies nine factors influencing risk perception. Nevertheless, it must be emphasized that we can continue to develop models and rules, but as long as the risk is not understood, we will never achieve anything.

Purpose: Entrepreneurial teams are one of the most crystallized forms of collaboration in the generically collective dynamics underpinning social entrepreneurship. Despite their quantitative prevalence, social entrepreneurial teams (SETs) remain quite absent from the scholarly literature. This chapter aims to develop a research agenda addressing this gap. Methodology/Approach: This chapter first reviews the scarce literature dealing with this subject and develops an operationalizable definition of SETs. Next, it confronts current knowledge on entrepreneurial teams with the specific context of social entrepreneurship to introduce and discuss main topics of investigation on SETs. Findings: Six topics are suggested to have a high potential for developing knowledge on SETs: formation, size and extended team, gender, decision-making and leadership, identity, and turnover. Research Implications: This chapter frames these research avenues within a developmental stages perspective with the aim to contribute to help form and maintain effective SETs. Originality/Value of Chapter: This research has implications for scholars as it defines SETs as a distinct object for research, which allows extending knowledge on collaborative dynamics in social entrepreneurship, but also on entrepreneurial teams in general. The suggested research agenda and its orientation toward the development of effective SETs should be a springboard for future research on this subject.

The purpose of this paper is to seek effective measurement methods that reflect the real value of process capital.

From a system model perspective, the authors refined the existing knowledge of process measurement by distinguishing three kinds of indicator for the value of process capital: input, output, and the capability to manage process capital. The design of this study, therefore, incorporates a longitudinal analysis of the content of process capital and traces its evolution by attaching a monetary value to activities and assets.

The tested results reveal that the input measure is a less effective measure for process capital, while the output measure is a valid one for measuring operational and managerial performance of process capital. The capability to manage process capital can predict all dimensions of process capital in both the short‐ and long‐term periods.

A practical view of process capital enhances the current understanding of process capital by highlighting the sustainability of process value and the validity of measuring output and management capability of the process capital. Second, the study results also explain the productivity paradox because of the complexity of the hidden cost of process input and the distinctive capability of organizations in managing technology and complementary resources. Finally, the system view of process capital, from input through process to output of the process capital, with operationalized measures, provides a useful reference for examining intellectual capital.

The findings offer a more robust definition of process capital as a firm's established capability to exploit the knowledge of business processes and organize resources in designing and managing business activities for sustained value.

The steady increase of data on human behavior collected online holds significant research potential for social scientists. The purpose of this paper is to add a systematic discussion of different online services, their data generating processes, the offline phenomena connected to these data, and by demonstrating, in a proof of concept, a new approach for the detection of extraordinary offline phenomena by the analysis of online data.

To detect traces of extraordinary offline phenomena in online data, the paper determines the normal state of the respective communication environment by measuring the regular dynamics of specific variables in data documenting user behavior online. In its proof of concept, the paper does so by concentrating on the diversity of hashtags used on Twitter during a given time span. The paper then uses the seasonal trend decomposition procedure based on loess (STL) to determine large deviations between the state of the system as forecasted by the model and the empirical data. The paper takes these deviations as indicators for extraordinary events, which led users to deviate from their regular usage patterns.

The paper shows in the proof of concept that this method is able to detect deviations in the data and that these deviations are clearly linked to changes in user behavior triggered by offline events.

The paper adds to the literature on the link between online data and offline phenomena. The paper proposes a new theoretical approach to the empirical analysis of online data as indicators of offline phenomena. The paper will be of interest to social scientists and computer scientists working in the field.