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Voluntary corporate social responsibility reporting has developed into an everyday activity for many commercial organizations, and scholarly interest in these practices continues to increase. This paper focusses on one subset of these disclosures, namely the figures relating to environmental expenditures and investments published by various organizations. The purpose of this paper is to provide insights into the nature, role and significance of such financial environmental information. Despite their seeming accuracy and preciseness, little is known about how such financial environmental information is constructed and subsequently used in organizational settings.

The paper is based on a qualitative case study focussing on a Finnish energy company. The authors build the investigation primarily on 26 semi-structured interviews with employees at all organizational levels, which the authors supplement with various documentary sources. The interpretation draws on the notion of loose coupling, which the authors use as a method theory to provide a better understanding of this complex organizational practice.

The authors highlight the ambiguous and imprecise nature of the outwardly accurate figures provided by the company. The authors argue that disclosed financial environmental information is only loosely coupled with various dimensions, including the organization’s actual activities, its environmental impacts and organizational decision making.

The findings contrast with those of some prior research, which has considered financial environmental information highly valuable. As for broader implications, the paper discusses the accuracy of public records based on such ambiguous organizational figures.

This study aims to test the effectiveness of a training intervention based on the psychology of perception, delivered to young Italian workers and employees, with low education, hired with an apprenticeship contract and involved in a compulsory training course (duration 32 h; the training intervention reported in the paper covers the first 8 h) whose aim was to let them develop such relational competencies as communication and cooperation with others.

By making use of optical-geometric illusions and ambiguous figures, participants were accompanied through a training intervention with the dual purpose of undermining their naive certainties about why they see what they see and increasing their awareness of how the perceptual processes work. At the beginning of the intervention, at the end of the 32 h (that is, after about a month) and after about one year from the end of the course, participants were administered a questionnaire to monitor the results of the training course by measuring their “perception awareness”.

“Perception awareness” increased from the beginning to the end of the course and still scored higher after one year. “Perception awareness” was positively related to communication and cooperation.

Although the literature is full of training courses delivered to improve communication and cooperation with others, little research has been carried out on perception-based training interventions delivered to young adults with low education hired with an apprenticeship contract for which this kind of training is compulsory.

The use of mixed-methods research (MMR) within building and construction research (BCR) is studied in detail. A new MMR paradigm, defined as ambiguous mixed-methods research (AMMR), is conceptualised within a BCR context. The paper aims to discuss these issues.

Informal and inductive methodology combines experiential and anecdotal knowledge with synthesis of extant literature, to detail a cogent representation of the BCR research paradigm continuum. From this, the AMMR design is presented and its conceptualisation highlighted by reference to a small sample of published BCR studies.

Paradoxically, the BCR paradigm continuum is dichotomous in its quantitative and qualitative extremes; while between these, coalesced paradigms permeate it. Influenced predominantly by worldview, many BCR researchers select a methodology that aligns with either continuum extreme. But, the authors conceptualise, in practice this often relies on ambiguous AMMR characteristics.

AMMR offers BCR research and beyond, a new approach for making, designing and defending methodological decisions.

The AMMR paradigm was designed by the authors and is therefore entirely novel.

Automatic segmentation of unorganized 3D human body scan data was developed without heuristic specified values. It was reliable in finding the upper body's primary landmarks. The paper aims to discuss these issues.

Quasi boundary point sequence (QBPS) was defined to find the boundary of the human body. Body scan data were categorized by clustering the features extracted from the predefined QBPS. A non-uniform rational B-spline (NURBS) approximation was used to detect the landmarks of the segmented upper torso.

The segmentation method based on feature extraction was reliable regardless of the scan data's fidelity. It was verified that the landmark detection method introduced in this work is more robust than a previous method that utilizes the position of point data.

There are several studies of human body segmentation and body landmark detection. This work, however, aims to automate fully segmentation and develop more reliable searching methods. Unlike previous work that uses only 2D human body information, this work uses 3D body information. Furthermore, previous landmark searching methods were superseded by more robust methods applying NURBS approximations.

Ontology in information studies consists of antinomic conceptions, methodologies, and emphases in both application and philosophizing. A comprehensive understanding of ontology in information studies can be achieved by employing Slavoj Žižek's parallax view which holds that reality is not only best understood by articulating conflicting perspectives on a particular phenomenon, but that given phenomena are fundamentally constrained by incommensurable perspectives that must be acknowledged accordingly. The paper aims to discuss these issues.

Ontology in information studies, including computational ontology development, is analyzed using critical information theory based on Heideggerian, poststructuralist, and anti-postmodern philosophy. The discussion is framed by Žižek's notion of the parallax Real.

A complete understanding of ontology in information studies that does not reduce ontology to a totalizing theory or sequester notions of ontology to conflicting, unrelated discourses, necessarily accepts articulating the alterity between differing ontological views as the means by which one can best allude to what “ontology in information studies really is.”

This paper presents a comprehensive analysis of radically different ontological perspectives on the nature of reality with respect to digital technology.

This article describes a course in interviewing skills for local authority auditors. It represents a further development of the “Bradford Approach” to interviewing skills training developed by Randell et al for appraisal interviewing and subsequently extended to include grievance interviewing by Gill. As such, it relies heavily on the notion that successful interviewing depends upon a number of precise behavioural skills which can best be acquired through practice in role plays. The course was developed at the request of the Internal Audit Section of Humberside County Council, who felt that existing courses for auditors did not provide adequate training in interviewing skills.

This study investigated the influence of ambiguous customer expectations and customer demandingness, which reflect hindrance and challenge demands, on the boundary spanning behaviors (BSBs) of frontline bank employees (FBEs) through person-job fit and work engagement. It also examined the moderating effect of customer stewardship between job demands and work engagement.

Data of 296 FBEs in the retail banking industry in the Republic of Korea were collected through an online survey and analyzed.

Ambiguous customer expectations acted as hindrance demands and negatively affected FBEs' psychological process. Additionally, customer demandingness positively affected FBEs' psychological process as challenge demands. Moreover, person-job fit and work engagement improved the BSBs of FBEs as a psychological motivation process. Lastly, customer stewardship buffered the negative influence of ambiguous customer expectations on work engagement while strengthening the positive influence of customer demandingness on work engagement.

This study contributes to the marketing literature by presenting customer-related characteristics influencing the BSBs of FBEs and exploring the psychological response processes. First, this study presents empirical evidence that ambiguous customer expectations and customer demandingness play the role of hindrance and challenge demands, respectively. Second, it confirms that customer-related characteristics affect the BSBs of FBEs through psychological processes. Finally, it enriches the authors' understanding of customer stewardship as a job resource by exploring the role of customer stewardship in moderating the relationship between different types of job demands and work engagement.

This paper aims to present a new term weighting approach for text classification as a text mining task. The original method, neutrosophic term frequency – inverse term frequency (NTF-IDF), is an extended version of the popular fuzzy TF-IDF (FTF-IDF) and uses the neutrosophic reasoning to analyze and generate weights for terms in natural languages. The paper also propose a comparative study between the popular FTF-IDF and NTF-IDF and their impacts on different machine learning (ML) classifiers for document categorization goals.

After preprocessing textual data, the original Neutrosophic TF-IDF applies the neutrosophic inference system (NIS) to produce weights for terms representing a document. Using the local frequency TF, global frequency IDF and text N's length as NIS inputs, this study generate two neutrosophic weights for a given term. The first measure provides information on the relevance degree for a word, and the second one represents their ambiguity degree. Next, the Zhang combination function is applied to combine neutrosophic weights outputs and present the final term weight, inserted in the document's representative vector. To analyze the NTF-IDF impact on the classification phase, this study uses a set of ML algorithms.

Practicing the neutrosophic logic (NL) characteristics, the authors have been able to study the ambiguity of the terms and their degree of relevance to represent a document. NL's choice has proven its effectiveness in defining significant text vectorization weights, especially for text classification tasks. The experimentation part demonstrates that the new method positively impacts the categorization. Moreover, the adopted system's recognition rate is higher than 91%, an accuracy score not attained using the FTF-IDF. Also, using benchmarked data sets, in different text mining fields, and many ML classifiers, i.e. SVM and Feed-Forward Network, and applying the proposed term scores NTF-IDF improves the accuracy by 10%.

The novelty of this paper lies in two aspects. First, a new term weighting method, which uses the term frequencies as components to define the relevance and the ambiguity of term; second, the application of NL to infer weights is considered as an original model in this paper, which also aims to correct the shortcomings of the FTF-IDF which uses fuzzy logic and its drawbacks. The introduced technique was combined with different ML models to improve the accuracy and relevance of the obtained feature vectors to fed the classification mechanism.

The first purpose of this paper is to situate and conceptualise ambiguity in the operations management (OM) literature, as connected to supply chain decision-making (SCDM). The second purpose is to study the role of ambiguity-coping mechanisms in that context.

This research uses the behavioural decision theory (BDT) to better embed ambiguity in a generic SCDM framework. The framework explicates both behavioural and non-behavioural antecedents of ambiguity and enables us to also ground the “coping” mechanisms as individual and organisational level strategies. Properties of the framework are illustrated through two “ambiguous” events – the 2011 Thai flood and Covid-19 pandemic.

Three key findings are documented. First, ambiguity is shown to distinctively affect supply chain decisions and having correspondence with specific coping mechanisms. Second, the conceptual framework shows how individual coping mechanisms can undermine rational-based organisational coping mechanisms, leading to “sub-optimal” (poor) supply chain decisions. Third, this study highlights the positive role of visibility but surprisingly organisational “experiential” learning is imperfect, due to the focus on “similar” past experience and what is known.

The paper is novel in two ways. First, it introduces ambiguity – an often neglected concept in operations management – into the supply chain lexicon, by developing a typology of ambiguity. Second, ambiguity-coping mechanisms are also introduced as both individual and organisational strategies. This enables the study to draw distinctive theoretical and practical implications.

Many REpresentational State Transfer (RESTful) Web services suffered from anti-patterns problem, which may diminish the sustainability of the services. The anti-patterns problem could happen in the code of the programme or the uniform resource identifiers (URIs) of RESTful Web services. This study aims to address the problem by proposing a technique and an algorithm for detecting anti-patterns in RESTful Web services. Specifically, the technique is designed based on URIs parsing process.

The study was conducted following the design science research process, which has six activities, namely, identifying problems, identifying solutions, design the solutions, demonstrate the solution, evaluation and communicate the solution. The proposed technique was embedded in an algorithm and evaluated in four phases covering the process of extracting the URIs, implementing the anti-pattern detection algorithm, detecting the anti-patterns and validating the results.

The results of the study suggested an acceptable level of accuracy for the anti-patterns detection with 82.30% of precision, 87.86% of recall and 84.93% of F-measure.

The technique and the algorithm can be used by developers of RESTful Web services to detect possible anti-pattern occurrences in the service-based systems.

The technique is personalised to detect amorphous URI and ambiguous name anti-patterns in which it scans the Web service URIs using specified rules and compares them with pre-determined syntax and corpus.