Why the epistemologies of trust researchers matter

In this thought piece we take stock of and evaluate the nature of knowledge production in the field of trust research by examining the epistemologies of 167 leading trust scholars, who responded to a short survey. Following a brief review of major epistemological perspectives we discuss the nature of the prevalent views and their geographical distribution within our field. We call on trust researchers to engage in epistemological reflection, develop their own awareness of alternative epistemologies, and ensure their work draws on and cites relevant research contrary to their preferred epistemological approach. To support this we ask editors of relevant journals to foster pluralism in trust research, publishing work from a range of epistemologies

Fast Computation of Smith Forms of Sparse Matrices Over Local Rings

We present algorithms to compute the Smith Normal Form of matrices over two families of local rings. The algorithms use the \emph{black-box} model which is suitable for sparse and structured matrices. The algorithms depend on a number of tools, such as matrix rank computation over finite fields, for which the best-known time- and memory-efficient algorithms are probabilistic. For an \nxn matrix $A$ over the ring \Fzfe, where $f^e$ is a power of an irreducible polynomial f \in \Fz of degree $d$, our algorithm requires \bigO(\eta de^2n) operations in \F, where our black-box is assumed to require \bigO(\eta) operations in \F to compute a matrix-vector product by a vector over \Fzfe (and $\eta$ is assumed greater than \Pden). The algorithm only requires additional storage for \bigO(\Pden) elements of \F. In particular, if \eta=\softO(\Pden), then our algorithm requires only \softO(n^2d^2e^3) operations in \F, which is an improvement on known dense methods for small $d$ and $e$. For the ring \ZZ/p^e\ZZ, where $p$ is a prime, we give an algorithm which is time- and memory-efficient when the number of nontrivial invariant factors is small. We describe a method for dimension reduction while preserving the invariant factors. The time complexity is essentially linear in $\mu n r e \log p,$ where $\mu$ is the number of operations in \ZZ/p\ZZ to evaluate the black-box (assumed greater than $n$) and $r$ is the total number of non-zero invariant factors. To avoid the practical cost of conditioning, we give a Monte Carlo certificate, which at low cost, provides either a high probability of success or a proof of failure. The quest for a time- and memory-efficient solution without restrictions on the number of nontrivial invariant factors remains open. We offer a conjecture which may contribute toward that end.Comment: Preliminary version to appear at ISSAC 201

The pervasiveness and implications of statistical misconceptions among academics with a special interest in business research methods

Statistics play a very important role in business research, particularly in studies that choose to use quantitative or mixed methods. Alongside statistical analysis, aspects related to research design (such as sampling, reliability and validity issues) require a good grounding in statistical concepts reinforced by careful practice to avoid potential mistakes arising from statistical misconceptions. Although quite a considerable number of published studies have focused on students' faulty thinking regarding statistical concepts, little research explores the extent to which these are also held by academics who are their instructors. This empirical study addresses this by answering the following questions: First, are statistical misconceptions pervasive among academics with a special interest in business research methods? If so, second, is there an association between the pervasiveness of statistical misconceptions and the preferred research tradition (qualitative, quantitative, mixed methods)?. Data were collected via a web questionnaire from a purposive sample of academics with an expressed interest in business research methods. The questionnaire comprised 30 categorical statements (agree, disagree, don't know) focusing on statistical misconceptions (and conceptions) relating to descriptive statistics, design strategies, inferential statistics and regression, and five demographic questions. We targeted a critical case purposive sample of 679 potential respondents. Although 166 consented to take part, only 80 completed the questionnaire and their responses form the basis of the statistical analysis, a response rate of 11.8 %. The study provides empirical evidence of both an absence of knowledge and a high pervasiveness of faulty notions that have infected the thinking of academics relating to both research design and the use of statistics. This is particularly so for academics who prefer quantitative methods, those preferring qualitative methods being more likely to admit that they do not know. The study argues that such lack of knowledge and misconceptions reduce the true utility of statistics in research. Recommendations are offered regarding the teaching of statistics within business research methods.peer-reviewe

Location Independent Working In Academia: Enabling employees or supporting managerial control?

In this article, we consider the extent to which the practice of location independent working (LIW) enables academic employees to make choices and have agency in their life-work balance, and the extent to which it may support (or potentially be used as a form of resistance to) increased managerial control. Set within the context of an increasingly performance-led, managerialist public sector landscape, the impact and implications of these working practices are examined through the lens of labour process theory. Drawing on findings from an ongoing in-depth ethnographic study set in a post-1992 university business school in central England, we suggest that the practice of LIW is being used both to enable employees and to support managerial control

Defining Early Positive Response to Psychotherapy: An Empirical Comparison Between Clinically Significant Change Criteria and Growth Mixture Modeling

Several different approaches have been applied to identify early positive change in response to psychotherapy so as to predict later treatment outcome and length as well as use this information for outcome monitoring and treatment planning. In this study, simple methods based on clinically significant change criteria and computationally demanding growth mixture modeling (GMM) are compared with regard to their overlap and uniqueness as well as their characteristics in terms of initial impairment, therapy outcome, and treatment length. The GMM approach identified a highly specific subgroup of early improving patients. These patients were characterized by higher average intake impairments and higher pre- to-posttreatment score differences. Although being more specific for the prediction of treatment success, GMM was much less sensitive than clinically significant and reliable change criteria. There were no differences between the groups with regard to treatment length. Because each of the approaches had specific advantages, results suggest a combination of both methods for practical use in routine outcome monitoring and treatment planning

Formulating a convincing rationale for a research study

Explaining the purpose of a research study and providing a compelling rationale is an important part of any coaching research project, enabling the work to be set in the context of both existing evidence (and theory) and its practical applications. This necessitates formulating a clear research question and deriving specific research objectives, thereby justifying and contextualising the study. In this research note we consider the characteristics of good research questions and research objectives and the role of theory in developing these. We conclude with a summary and a checklist to help ensure the rationale for a coaching research study is convincing

Success in challenging times: Key lessons for UK SMEs (summary report)

There are approximately 4.5 million small businesses in the UK providing 13.7 million jobs, half the private sector workforce in 2011. However, while Small and Medium Enterprises (SMEs) are of importance, it is their durability that can be considered of greater significance. The precarious nature of SME existence has been well documented. Only about 65% of small businesses are still trading after the first three years of initial start-up. After five years, less than 45% of businesses will have survived. Put simply, small firms are more likely to die than larger firms. Indeed, other than size per se, the higher likelihood of death is what distinguishes small from large firms. Much of the research into small firms has focused on their failure. The danger of this approach is that it identifies what has gone wrong, but may fail to discover what they need to do right. The approach of the current study, then, is to focus on the triggers that lead to SME success, as a way of highlighting more effective strategy decisions for firms themselves, and to inform better policy decisions for government. A return of over 1000 survey questionnaires completed by SME owners/directors or senior managers, 20 in depth interviews and 14 focus groups, makes this one of the largest surveys into the strategic management of SMEs in the UK

SME success in challenging times: Bank finance - lost in translation

The conventional wisdom, not just in the UK but also internationally, is that the major banks are not interested in lending to small and medium-sized enterprises (SMEs). One of the main factors cited is that banks find it difficult to gauge whether SMEs have the capacity and/or willingness to repay their debts. In contrast, some studies suggest that most SMEs seeking external funding are successful in their applications. The current study sets out to investigate the truth of these seemingly contradictory claims and makes recommendations for improvements in SME access to bank finance. In conducting the study, the authors made use of their 2012 national survey on the triggers for SME success (with over 1,000 SME responses), and secondary data analysis of government reports, with new data gathering methods using two SME focus groups, five in-depth SME case studies, and analysis of the major banks’ SME lending policies as presented through their websites. Access was obtained to interview the senior lending policy makers of four major banks and one challenger bank. Research revealed that the majority of SMEs seeking routes to finance avoid banks and traditional financial institutions. The main source of finance used by SMEs to start their business is personal/family savings, with more established SMEs using retained profits. Although banks are used by SMEs, they are not the primary source of finance. From an SME perspective, not only do banks not provide the capital required, but they also seem to know very little about what businesses (particularly small businesses) need. However, the picture is more nuanced than this. Of those SMEs that seek access to external finance, banks are still the primary source. Furthermore, and contrary to popular myth, the majority of SMEs seeking finance from banks do obtain it. This situation, however, has deteriorated. Before the economic crisis of 2008, 90% of SMEs seeking bank finance successfully attained it, a figure which fell to 74% in 2011. This partly helps to explain the growth in importance of alternative sources of finance such as business angels, peer-to-peer lending and crowd funding. Drawing upon the literature reviewed, the two focus groups with SMEs, and the five bank interviews, a number of key findings were derived