Uncertainty and previvors’ cancer risk management: understanding the decision-making process

Women who test positive for a BRCA genetic mutation, but who have not been diagnosed, or 'previvors,' experience intense, chronological risk-related uncertainty. Women’s risk management medical decisions can be a way to manage their uncertainty, but little is known about how uncertainty informs their decision or how uncertainty is impacted by these medical decisions. Using an uncertainty management theoretical lens, we interviewed 46 previvors about their decision-making process. A thematic analysis revealed two uncertainty management (i.e., risk-reducing) decision-making pathways (preventive surgery and increased surveillance) with each pathway encompassing a three-part process of 1) uncertainty appraisal, 2) medical decision (i.e., uncertainty management strategy), and 3) outcomes. The findings advance theoretical thinking about uncertainty and risk management as an ongoing, distressful chronic experience, and highlight the importance of life-span phenomena in women’s decision-making process. Based on the findings, we constructed a translational tool to aid genetic counselors and previvors facing these medical decisions.     

Rational actions or institutional actions: A study on the rationality in academic librarians' decision-making processes when purchasing e-book products

It is important for academic librarians to demonstrate that they are trusted stewards of public money when purchasing e-book products; however, prior studies seldom examine the rationality in librarians' decision-making processes. Interviews including 20 librarians from 19 different institutions were conducted to collect data about their decision-making processes when purchasing e-book products. Institutional theory was used as a framework to analyze interview data. Librarians' perceptions of the environment where their decision process occurred were described as full of uncertainty, with the e-book market viewed as non-competitive with limited alternative products. Seven strategies the interviewees adopted to justify their purchase decisions were then identified, including experimentation, incorporating users' input, reliance on written documents, learning from past experiences, learning from other libraries, group decision, and aggressive negotiation. Decision-making processes were a mixture of institutional and rational actions. Factors affecting rationality in librarians' e-book purchase decisions could be applied to other types of decision-making in library settings, allowing stakeholders to better understand and interpret the situations that either help or hinder the rationality in library's decision-making.     

Professionals: their problems, their fears, and their social responsibilities

Professional societies have been reluctant to enter actively into the public processes by which decisions are made on economic, social, and political issues. This reluctance comes from (1) fears about the status of the profession and the professional society, (2) fears about economic reprisal, (3) potential conflicts between the goals of a philosophy of trade unionism and the goals of a philosophy of professional social responsibility, and (4) domination of some professional societies by nonprofessional business, industrial, or administrative groups. This reluctance has been justified by the development of a myth that the professional can exercise individual social responsibility while maintaining the neutrality of his institutions and societies. This myth must be ignored because our public decision-making processes can only function properly if groups, such as professional societies, actively enter that decision-making process.     

Automated decision-making and good administration: Views from inside the government machinery

Use of semi- and fully automated, administrative decision-making in public administration is increasing. Despite this increase, few studies have explicitly analysed its relation to good administration. Good administration is regulations and norms aimed at securing the correctness of administrative decisions as well as the legitimacy of these and is often associated with underlying values such as transparency, equality of treatment and accountability. Based on a thematic analysis of qualitative interviews with 43 key public administration stakeholders in a wide array of policy areas in Denmark, insiders of government machinery are shown to perceive relations between automated decision-making and good administration as manifold. Automated, administrative decision-making is articulated as providing both opportunities for supporting good administration and undermining good administration. Six values of good administration particularly related to automated, administrative decision-making are identified: Carefulness; Respecting-individual-rights; Professionalism; Trustworthiness; Responsiveness and Empowerment. Put simply, risks to good administration can be expected to occur if administrative bodies apply automated, administrative decision-making, while opportunities must be actively nurtured through managerial attention. Despite popular conceptions of the threat of “robotic government”, the conclusions of this study indicate a need for a more pragmatic view of relations of automated, administrative decision-making and good administration balanced between outright techno-optimism and techno-pessimism.     

The impact of using algorithms for managerial decisions on public employees' procedural justice

Algorithms are used in public management decisions, for instance, to allocate police staff to potential crime scenes. We study how the usage of algorithms for managerial decisions affects procedural justice as reported by public employees. We argue that some public management practices may be more suitable for algorithmic decision-making than others. We hypothesize that employees' perceptions differ depending on the complexity of the practice at hand. We test this through two survey experiments on 109 Dutch public employees and 126 public employees from the UK. Our results show that when a decision is made by an algorithm for practices that are low in complexity, procedural justice increases. Our results also show that, for practices that are high in complexity, decisions involving a public manager are perceived as higher in procedural justice compared to decisions that were made automatically by computers using algorithms. Nevertheless, adding an algorithm to a public manager's decision-making process can increase procedural justice for high complexity practices. We conclude that managers should explore automation opportunities for low complexity practices, but to be cautious when using algorithms to replace public managers' decisions for high complexity practices. In the latter case, transparency about algorithms and open dialogues on perceptions could be beneficial, but this should not be seen as a panacea.     

Understanding issues with stakeholders participation processes : A conceptual model of SPPs' dimensions of issues

Over the last decade, expanded participation among stakeholders has been increasingly adopted by both public and private organizations in different domains. This approach is used to strengthen the involvement of stakeholders in decision-making processes about meaningful decisions that will affect their communities. This paper aims to review, categorize, and offer a better understanding of the different issues that stakeholders' participation processes (SPPs). To meet this aim, a systematic literature review has been conducted. This paper has two main contributions. First, it presents a typology of issues that is arranged in nine categories: economic, efficiency and effectiveness, ethical, legislative, political, administration, socioeconomic, stakeholders and social, and technology. Second, it proposes a conceptual model of SPPs dimensions of issues. A real-world scenario of use of the proposed conceptual model and recommendations are presented.     

The perils and pitfalls of explainable AI: Strategies for explaining algorithmic decision-making

Governments look at explainable artificial intelligence's (XAI) potential to tackle the criticisms of the opaqueness of algorithmic decision-making with AI. Although XAI is appealing as a solution for automated decisions, the wicked nature of the challenges governments face complicates the use of XAI. Wickedness means that the facts that define a problem are ambiguous and that there is no consensus on the normative criteria for solving this problem. In such a situation, the use of algorithms can result in distrust. Whereas there is much research advancing XAI technology, the focus of this paper is on strategies for explainability. Three illustrative cases are used to show that explainable, data-driven decisions are often not perceived as objective by the public. The context might raise strong incentives to contest and distrust the explanation of AI, and as a consequence, fierce resistance from society is encountered. To overcome the inherent problems of XAI, decisions-specific strategies are proposed to lead to societal acceptance of AI-based decisions. We suggest strategies to embrace explainable decisions and processes, co-create decisions with societal actors, move away from an instrumental to an institutional approach, use competing and value-sensitive algorithms, and mobilize the tacit knowledge of professionals     

Rationality and politics of algorithms. Will the promise of big data survive the dynamics of public decision making?

Big data promises to transform public decision-making for the better by making it more responsive to actual needs and policy effects. However, much recent work on big data in public decision-making assumes a rational view of decision-making, which has been much criticized in the public administration debate. In this paper, we apply this view, and a more political one, to the context of big data and offer a qualitative study. We question the impact of big data on decision-making, realizing that big data – including its new methods and functions – must inevitably encounter existing political and managerial institutions. By studying two illustrative cases of big data use processes, we explore how these two worlds meet. Specifically, we look at the interaction between data analysts and decision makers. In this we distinguish between a rational view and a political view, and between an information logic and a decision logic. We find that big data provides ample opportunities for both analysts and decision makers to do a better job, but this doesn't necessarily imply better decision-making, because big data also provides opportunities for actors to pursue their own interests. Big data enables both data analysts and decision makers to act as autonomous agents rather than as links in a functional chain. Therefore, big data's impact cannot be interpreted only in terms of its functional promise; it must also be acknowledged as a phenomenon set to impact our policymaking institutions, including their legitimacy.     

Non-governmental health statistics on the World Wide Web

Health statistics are an important decision-making resource for professionals and consumers alike. Professional use of statistics is wide ranging and often includes legislative decision making, medical research, grant writing, and population analysis. Locating needed or even helpful statistics to make these decisions or analyses can seem overwhelming. Organizations advocating for the treatment or assessment for particular diseases and health conditions are a prime resource for needed statistics. This column describes links and provides summaries to organizations that offer statistical resources for many of the leading causes of disability and death; it is the second of two columns devoted to finding health statistics on the Web. A helpful search strategy is presented which includes the utilization of evaluative criteria to seek legitimate and credible information.     

Techno-optimism and policy-pessimism in the public sector big data debate

Despite great potential, high hopes and big promises, the actual impact of big data on the public sector is not always as transformative as the literature would suggest. In this paper, we ascribe this predicament to an overly strong emphasis the current literature places on technical-rational factors at the expense of political decision-making factors. We express these two different emphases as two archetypical narratives and use those to illustrate that some political decision-making factors should be taken seriously by critiquing some of the core ‘techno-optimist’ tenets from a more ‘policy-pessimist’ angle. In the conclusion we have these two narratives meet ‘eye-to-eye’, facilitating a more systematized interrogation of big data promises and shortcomings in further research, paying appropriate attention to both technical-rational and political decision-making factors. We finish by offering a realist rejoinder of these two narratives, allowing for more context-specific scrutiny and balancing both technical-rational and political decision-making concerns, resulting in more realistic expectations about using big data for policymaking in practice.     

Librarians at the Bounds of Rationality: How Bounded Rationality Can Help Us Help Others

“Bounded rationality” is a concept used in the social sciences to help identify and predict how individuals make decisions. An offshoot of rational choice theory, bounded rationality accounts for the fact that completely rational decisions are not feasible in practice and states that individuals use heuristics, or rules based on past experiences and information, to make decisions. The disciplinary home of bounded rationality is behavioral economics, but this concept is becoming more popular in other branches of the social sciences to help explain and predict human behavior. We can benefit from looking at librarianship from the perspective of bounded rationality, which has been done infrequently in our professional literature. Bounded rationality can explain how our users create heuristic shortcuts to simplify the decision-making process and deal with the multitude of choices and information available. If we can understand and harness these heuristics, we will better understand how our users make decisions and better determine how we can assist them. Moreover, librarians could also be said to make decisions using bounded rationality. Tasks such as collection development and the reference interview involve the use of heuristics on our part to process all the information we have available to us. Becoming aware of this process can provide for a more mindful and efficient way of making choices. This concept article will describe bounded rationality, apply bounded rationality to aspects of library service, and discuss the possible use of the concept as an assessment tool for our services.     

User experience of government documents: A framework for informing design decisions

People still use documents in many everyday government processes. From tax payments to passport requests, citizens have to interact with low-interactivity information artifacts such as reports, maps and datasets, among many others. Despite efforts to improve information delivery in the public sector, effective information usage remains a critical topic of action and research. The user experience of government documents has rarely been assessed, despite them being regularly published and frequently used. Considering this, the two following research questions arise: 1) How can government documents be classified (or grouped) in terms of user experience? 2) How can the user experience of government documents be monitored over time in order to inform design decisions? Working with a public agency in Chile, we develop and test a classification and monitoring framework based on two online surveys (N?=?338 and N?=?298). We then propose a framework for understanding user experience of government documents in these three dimensions: interaction goal, volume of information and ease of understanding. Using a graphical representation to classify user experience provides greater visibility of the current status of information produced by a public organization. Furthermore, by monitoring the user experience of a government document at different times, organizations can understand the effect of their design decisions and improve their service quality by implementing user-centered processes.     

Participative Democracy and Voice: Rethinking Community Collaboration Beyond Neutral Structures

Decision-making in community-based, interorganizational collaboration often influences educational, environmental, and other civic policies thereby constituting it as politically and socially consequential. As such, we rethink collaboration through the lens of participative democracy rather than as a neutral organizational structure or process. We sought to understand how participative democracy was hindered and accomplished in an interpretive case study of two community collaborations. Data indicate the normative processes and structures of communication practiced by stakeholders primarily deterred voice and participation by prioritizing information exchange, practicing invisible decision-making, and emphasizing harmonious relationships. These findings: (1) add to theories of interorganizational collaboration by establishing voice as both a discursive and political feature of shared decision-making; (2) provide empirical exemplars that extrapolate political and social implications from specific communication practices; and (3) inform the development of a heuristic to improve collaborative participation and increase political accountability. Flowing from these data, we recommend practitioners utilize the heuristic of VOICE—promoting visibility and ownership of decision-making processes, less emphasis on informing, and purposeful fostering of gracious contestation—ultimately delimiting expressive modes of communication that decrease participative democracy and political accountability.     

Parents’ information seeking during adolescent career development: a test of the theory of motivated information management

Parents are an important source of advice when adolescents are faced with decisions about postsecondary education and career planning; however, parents often need to seek information to facilitate their child’s career development. This study applies the theory of motivated information management (TMIM) to evaluate the decision-making process parents undergo in this context and tests the boundaries of TMIM by considering how individuals use face-to-face (FtF) and online sources to alleviate uncertainty-related anxieties. A community sample of parents (N?=?937) completed a survey regarding their information seeking behaviors surrounding their adolescent’s career development. Parents reported using both FtF and online sources to seek information about their child’s postsecondary plans, and they engaged in different evaluative processes depending on the source of information. Theoretical implications related to TMIM and practical implications related to parents as sources of information in adolescent career development are discussed.     

Radio Reverb: The Impact of “Local” News Reimported to Its Own Community

According to recent data, more than 40% of radio stations now do news for stations outside their own market. This “outsourced news,” as one former Federal Communications Commission commissioner called it, raises questions about how local news decisions are made when removed from their local context. Using research on news conventions and decision-making processes, and data from field work in a small radio market served by news produced in a large market, this study frames issues of news selection and presentation within the context of a deregulated environment where the lines of what is “local” in local news are blurring.     

Data science empowering the public: Data-driven dashboards for transparent and accountable decision-making in smart cities

Dashboards visualize a consolidated set data for a certain purpose which enables users to see what is happening and to initiate actions. Dashboards can be used by governments to support their decision-making and policy processes or to communicate and interact with the public. The objective of this paper is to understand and to support the design of dashboards for creating transparency and accountability. Two smart city cases are investigated showing that dashboards can improve transparency and accountability, however, realizing these benefits was cumbersome and encountered various risks and challenges. Challenges include insufficient data quality, lack of understanding of data, poor analysis, wrong interpretation, confusion about the outcomes, and imposing a pre-defined view. These challenges can easily result in misconceptions, wrong decision-making, creating a blurred picture resulting in less transparency and accountability, and ultimately in even less trust in the government. Principles guiding the design of dashboards are presented. Dashboards need to be complemented by mechanisms supporting citizens' engagement, data interpretation, governance and institutional arrangements.     

IT portfolio decision-making in local governments: Rationality,politics, intuition and coincidences

IT project portfolio management (IT PPM) has evolved into a significant area of research interest, but we know little about IT PPM practices in public sector organizations. Therefore this article investigates decision-making processes in the IT PPM practices of local governments, and discusses how these practices match the normative advice proposed by the IT PPM literature. We rely on decision-making theories together with case-studies of four Danish local governments. We find that politics, intuition and coincidence play a crucial role in IT PPM decision-making, while technical rationality (as proposed by the IT PPM literature) plays a minor role. Our account also reveals how the decision-making practices create IT portfolio problems and in some aspects is considered to have a negative impact on the outcome of e-government investments. Our analysis and previous research into decision-making allows us to argue that implementing textbook-IT PPM is difficult because it relies on decision-making ideals that are incompatible with organizational contexts and individual behavior in these organizations. Instead of radically changing decision-making styles, the organizations might be better off improving IT PPM practice within the boundaries of their existing decision-making styles, and the IT PPM literature might improve support for practitioners by incorporating other decision-making styles besides technical rationality.     

A test of the initial processes of the goal‐planning‐action model of interpersonal influence

Dillard's goals‐planning‐action (GPA) model of interpersonal influence encompasses two different process models depending on the initial weighing of primary and secondary goals. In contrast to the GPA's prediction that the ordering of the intervening processes is moderated by the initial weighing of these two types of goals, a simplified version was found that fit the data both when the primary goal was greater than the secondary goal and when the secondary goal was greater than the primary goal. In both conditions, the two types of goals have simultaneous, direct relationships with the persuaders’ decisions to engage their targets, and indirect effects on subsequent plan generation.     

‘You get in a hole,it’s like quicksand’: a grounded theory analysis of social support amid materially bounded decision-making processes*

Financial precarity is a reality for a significant portion of the U.S. population. The inability of people to live sustainably has wide-ranging ramifications for individuals, families, communities, and larger society. The lived experiences of those in low-income financial precarity is perpetually threatened and constrained from a material standpoint. In this grounded theory research, we analyzed the perceived manifestation of social support during financially precarious decision-making. This study contributes the notion of materially bounded decision-making as a theoretical concept that foregrounds the role of materiality in decision-making processes. The analysis revealed uncertainty, urgency, complexity, and risk as the underlying context for materially bounded decision-making. Depending on the strength or weakness of participants’ social support systems, the trajectory of decision-making processes changes, leading to two dominant decision-making pathways. Results indicated that at times communicative social support intervention provided a sense of temporary stability.