bluuebunny/crossref_metadata_2025_split huggingface dataset:
Demanding dialogue in an unsettled settler state: implications for education and justice
Authors: Rudolph Sophie 
Published: November 2020

Purpose:The purpose of this paper is to examine the educational impulses and effects of Indigenous dialogue with the settler colonial state. Taking the Uluru Statement from the Heart, devised in May 2017 by a convention of Aboriginal and Torres Strait Islander peoples, as a starting point, and contrasting this with the 1967 Referendum campaign for constitutional reform, the paper explores the role of multiple forms and contexts of education during these processes of First Nations dialogue with the settler state.Design/methodology/approach:This paper draws on historical accounts of the 1967 Referendum and the 2017 Uluru Statement from the Heart.Findings:The paper demonstrates how education provided by the state has been used by First Nations peoples to challenge education systems and to dialogue with the settler state for Indigenous recognition and rights. It also illuminates the range of views on what education is and should be, therefore, contesting the neat and settled conceptions of education that can dominate policy discourse. Finally the historical cases show the deficiencies of settler state education through its failure to truthfully represent Australian history and its failure to acknowledge and confront the entirety of the consequences of settler colonial practices.Originality/value:This paper seeks to bring issues of education, politics and justice together to illustrate how the settler state and its institutions – specifically here, education – are part of an ongoing project of negotiation, contestation and dialogue over questions of justice.
Chronic pain management a fundamental human right: adaptation and examination of psychometric properties of pain anxiety symptoms scale among osteoporosis sample from Pakistan
Authors: Shuja Kanwar Hamza , Aqeel Muhammad , Sarfaraz Rimsha 
Published: November 2020

Purpose
Chronic pain is a global community health and human rights issue. Proper health care is an important necessity for every human being and access for treatment is every human’s right. Likewise, it is significant that proper instruments should be administered to assess these clinical issues. It is equally necessary to reassess these tools accordingly to diverse cultures, especially subjective tools to check their validity and cultural specification. The purpose of this study is to adapt and examine the factorial structure of 20 items and three-factor structure, pain anxiety symptoms scale (McCracken and Dhingra, 2002). As literature evidence suggested of a three-factor structure (Cho, 2010).

Design/methodology/approach
Primarily, the scale was translated into Urdu language using the forward-backward method. Afterward, a reliability assessment and a confirmatory factor analysis (CFA) for construct validity, on an osteoporosis patients’ sample (N = 250) was performed. Subsequently, an Obliman method exploratory factor analysis (EFA) was conducted on an osteoporosis sample (N = 500) for factor structuring followed by validity and reliability analysis.

Findings
The initial findings demonstrated a high internal consistency of the translated version of the scale (α = 0.85) and an acceptable test-retest reliability (r = 0.69). CFA displayed a high inter-correlation between scale and its subscales. However, CFA suggested a three-factor model. Consequently, EFA proposed a three-factor, 19 item scale, namely, behavioral; cognitive; and physical subscale, which demonstrated high alpha reliability (α.= 0.86). Other results indicated the scale to have a significant predictive and convergent validity for depression and positive and negative affect.

Originality/value
The present study is novel in its approach as the present study not only tried to adapt the original Pain Anxiety Symptom Scale to Pakistani culture but has also checked the factorial structure of the original scale. The results achieved in the process suggested a three-factor structure scale with 19 items in opposition to the original four structured, 20 items scale.
A case-study to examine doctors’ intentions to use IoT healthcare devices in Iraq during COVID-19 pandemic
Authors: Alhasan Ameer , Audah Lukman , Ibrahim Ishaq , Al-Sharaa Ammar , Al-Ogaili Ali Saadon , M. Mohammed Jabiry 
Published: November 2020

Purpose
Several countries have been using internet of things (IoT) devices in the healthcare sector to combat COVID-19. Therefore, this study aims to examine the doctors’ intentions to use IoT healthcare devices in Iraq during the COVID-19 pandemic.

Design/methodology/approach
This study proposed a model based on the integration of the innovation diffusion theory (IDT). This included compatibility, trialability and image and a set of exogenous factors such as computer self-efficacy, privacy and cost into the technology acceptance model comprising perceived ease of use, perceived usefulness, attitude and behavioral intention to use.

Findings
The findings revealed that compatibility and image of the IDT factors, have a significant impact on the perceived ease of use, perceived usefulness and behavioral intention, but trialability has a significant impact on perceived ease of use, perceived usefulness and insignificant impact on behavioral intention. Additionally, external factors such as privacy and cost significantly impacted doctors’ behavioral intention to use. Moreover, doctors’ computer self-efficacy significantly influenced the perceived ease of use, perceived usefulness and behavioral intention to use. Furthermore, perceived ease of use has a significant impact on perceived usefulness and attitude, perceived usefulness has a significant impact on attitude, which, in turn, significantly impacting doctors' behavior toward an intention to use.

Research limitations/implications
The limitations of the present study are the retractions of the number of participants and the lack of qualitative methods.

Originality/value
The finding of this study could benefit researchers, doctors and policymakers in the adaption of IoT technologies in the health sectors, especially in developing counties.
Visualizing differential principal turnover
Authors: Davis Bradley , Anderson Erin 
Published: November 2020

PurposeThe authors demonstrate the usage of data visualization for conveying educational administration research, with a specific focus on differential principal turnover. They model when and how principals move, over time, between six categories of turnover.Design/methodology/approachThe authors construct several easy-to-interpret alluvial diagrams that reveal the patterns of differential turnover among 1,113 first-time Texas principals. Furthermore, the authors investigate how these patterns differ across educator characteristics (i.e. race and sex) and school contexts (i.e. school level and campus urbanicity).FindingsHalf of all first-time principals turn over within two years. Most principals who stay in leadership roles leave the district where they were first entered the principalship. Men are promoted more and women turn over less. In a connected finding, the authors conclude that elementary principals turn over less, and middle and high school principals are promoted more often. Principals of color are demoted more often than White principals. Urban school principals exit the system at a greater rate than rural principals.Originality/valueThe significance of this study lies in its direct response to two problems facing the administrator turnover knowledge base – a lack of methodological accessibility and the underutilization of data visualization. The authors’ is the first study to contain visualization of differential turnover outcomes over time. Second, the authors’ study provides a blueprint for data visualization that not only creates new knowledge but also speaks to a wider variety of education stakeholders by presenting complex data in a visual format.
Estimating the value, ownership structure and turnover rate for investible commercial real estate from transaction datasets
Authors: Devaney Steven , Scofield David 
Published: November 2020

PurposeCommercial real estate (CRE) is a major investment asset. Yet detailed information on the value of investible CRE in different cities is lacking. The authors propose an innovative method to measure the value of investible CRE using transaction datasets.Design/methodology/approachThe authors take transaction prices and index them to produce a time series of values for each asset. The sum of the values at each point represents the value of investible CRE at that date. The authors’ method is applied to transaction data for New York, London and Toronto.FindingsLondon had the highest proportions of institutional and foreign ownership, and its turnover was more resilient to the downturn in global CRE following the GFC. The results illustrate the potential of the authors’ method to shed light on the characteristics of investible CRE markets.Research limitations/implicationsThe authors use data from Real Capital Analytics (RCA). This provides good coverage of transactions for investible CRE in the cities that the authors examine, but data from other sources might lead to different estimates.Practical implicationsMeasuring the value and turnover of investible CRE is important for portfolio strategies that account for the size and liquidity of investment markets. Knowledge of these features, and of ownership patterns, provides a better understanding of market operation.Originality/valueThe authors’ modification of the perpetual inventory technique is simple, novel and practical. The authors propose this approach given the absence of a building-by-building inventory of investible CRE in many markets.
Cost overruns and delays in infrastructure projects: the case of Stuttgart 21
Authors: Steininger Bertram I. , Groth Martin , Weber Brigitte L. 
Published: November 2020

PurposeWe investigate causes for the cost overrun and delay of the railway project Stuttgart 21. Besides, we try to forecast the actual costs and completion date at an early stage.Design/methodology/approachThe results of exploratory research show the causes for the cost overrun and delay of Stuttgart 21; we compare our findings with other railway projects. To estimate the costs at an early stage, the reference class forecasting (RCF) model is applied; to estimate the time, we apply an OLS regression.FindingsWe find that the following causes are relevant for the cost overrun and delay of Stuttgart 21: scope changes, geological conditions, high risk-taking propensity, extended implementation, price overshoot, conflict of interests and lack of citizens' participation. The current estimated costs are within our 95% confidence interval based on RCF; our time forecast underestimates or substantially overestimates the duration actually required.Research limitations/implicationsA limitation of our approach is the low number of comparable projects which are available.Practical implicationsThe use of hyperbolic function or stepwise exponential discount function can help to give a clearer picture of the costs and benefits. The straightforward use of the RFC for costs and OLS for time should motivate more decision-makers to estimate the actual costs and time which are necessary in the light of the rising demand for democratic participation amongst citizens.Social implicationsMore realistic estimates can help to reduce the significant distortion at the beginning of infrastructure projects.Originality/valueWe are among the first who use the RCF to estimate the costs in Germany. Furthermore, the hyperbolic discounting function is added as a further theoretical explanation for cost underestimation.
How do mid-level managers experience data science disruptions? An in-depth inquiry through interpretative phenomenological analysis (IPA)
Authors: Sengupta Atri , Mittal Shashank , Sanchita Kuchi 
Published: November 2020

PurposeRapid advancement of data science has disrupted both business and employees in organizations. However, extant literature primarily focuses on the organizational level phenomena, and has almost ignored the employee/individual perspective. This study thereby intends to capture the experiences of mid-level managers about these disruptions vis a vis their corresponding actions.Design/methodology/approachIn a small-sample qualitative research design, Interpretative Phenomenological Analysis (IPA) was adopted to capture this individual-level phenomenon. Twelve mid-level managers from large-scale Indian organizations that have extensively adopted data science tools and techniques participated in a semi-structured and in-depth interview process.FindingsOur findings unfolded several perspectives gained from their experiences, leading thereby to two emergent person-job (mis)fit process models. (1) Managers, who perceived demands-abilities misfit (D-A misfit) as a growth-alignment opportunity vis a vis their corresponding actions, which effectively trapped them into a vicious cycle; and (2) the managers, who considered D-A misfit as a psychological strain vis a vis their corresponding actions, which engaged them into a benevolent cycle.Research limitations/implicationsThe present paper has major theoretical and managerial implications in the field of human resource management and business analytics.Practical implicationsThe findings advise managers that the focus should be on developing an organizational learning eco-system, which would enable mid-level managers to gain their confidence and control over their job and work environment in the context of data science disruptions. Importantly, organizations should facilitate integrated workplace learning (both formal and informal) with an appropriate ecosystem to help mid-level managers to adapt to the data-science disruptions.Originality/valueThe present study offers two emergent cyclic models to the existing person–job fit literature in the context of data science disruptions. A scant attention of the earlier researchers on how individual employees actually experience disruption, and the corresponding IPA method used in the present study may add significant value to the extant literature. Further, it opens a timely and relevant future research avenues in the context of data science disruptions.
Critical realism and attribution theory in qualitative research
Authors: Al-Sharif Rami 
Published: November 2020

PurposeThe aim of this paper is to develop an integrative model that explains how incorporating the two epistemological positions of critical realism and attribution theory can help qualitative organisational researchers better understand the reality of social actors through different lenses. In addition, the paper aims to demonstrate the application of the model through a study of organisational justice perceptions of elite Muslim professionals undergoing performance appraisal in the UK banking sector.Design/methodology/approachThe approach adopted used semi-structured in-depth interviews with Muslim professionals in elite positions in UK Western and Islamic banks. Access to participants was secured through a process of purposive and snowball sampling, a tool often used to recruit hard-to-reach populations. The data were analysed through the integrative model developed in this paper.FindingsThe integration of critical realism and attribution theory provided different dimensionalities of social reality. Attribution theory enabled a systematic identification of social phenomena and their causal mechanisms, defined the characteristics of those mechanisms and highlighted who/what is responsible for and affected by them. Critical realism distinguished between causal mechanisms and the generative forces that help those mechanisms to be actualised and have effect.Originality/valueThe contribution of this paper is twofold. First, to the best of my knowledge, it is the first paper to build a novel integrative model of these two epistemologies. Second, it presents a detailed application of the model in a contemporary study of the perceptions of justice of Muslims in the UK banking sector.
Pharmaceutical/high-tech alliances; transforming healthcare?
Authors: Vermeer Laurence , Thomas Mark 
Published: November 2020

Purpose
Digitalization is changing businesses everywhere and the healthcare sector is no exception to this (r)evolution. Yet history teaches us that radical innovation rarely comes from within the industry. Big pharma is a potential victim of this rule. Its leaders should be worried. Some are already. The industry needs to develop its digital capabilities. Alliances with high tech companies may help this process.

Design/methodology/approach
The article adopts a critical analysis approach of alliances between the pharmaceutical and high-tech industries. The viewpoint is supported by revelatory case studies. Examples include Amazon and Pillpack as well as Google’s launch of Verily and Calico. Alliances between Novartis and Microsoft and Amazon as well as GSK and Google also provide supporting evidence.

Findings
Pharmaceutical companies are lagging behind in digital transformation. A recent McKinsey report found that the industry was well below the travel, hospitality and retail sectors in digitalization. It was barely more advanced that the public sector. Given the financial and intellectual resources within big pharma, this result seems nothing short of stunning.

Originality/value
This article offers an evidence-based viewpoint on the current state of digitalization within the pharmaceutical industry. It demonstrates the danger that high-tech companies present to big pharma and offers advice on how they may counteract such risks through alliances.
Humming noise reduction of ceiling fan in the mass production applying DMAIC-six sigma approach
Authors: Ahammed Rubel , Hasan Md. Zahid 
Published: November 2020

PurposeSuccess and business reputation depend upon the quality of products where product quality depends upon the capability of a process, yield value and sigma score, etc. Poor quality of ceiling fan and mass rejection from quality check resulted in an alarming amount of cost for rework. As a result, the fulfillment of the production target was getting difficult day by day. The main purpose of this research is to identify the crucial causes for humming noise of ceiling fans and control it to a tolerable level so that maximum quality can be achieved.Design/methodology/approachThe poor quality of ceiling fans was determined from the Pareto analysis of the define, measure, analyze, improve and control model which was humming noise during running and further actions were undertaken regarding the reduction of the humming noise. Project charter was formed before initiating the measure phase to study the suppliers, inputs, processes, outputs and customers diagram with process parameters and existing noise data were collected from random samples to determine the rolled throughput yield (94.95% existing) and existing sigma score which value of 3.14 and also the poor value (1.05) of process potential index implied that the process condition was below standard (<1.33) and need to be improved badly. Then root causes analysis and relationship diagram was prepared to identify the possible causes and with the design of experiments and correlation analysis, it was clear that the air gap between the stator and rotor was the main culprit behind the humming noise.FindingsThe minimum value of air gap was determined from boxplot analysis which was 0.2 mm–0.225 mm and the corresponding mean, the minimum and maximum value of sound level in dB (37.5–40.3 dB) for 0.225 mm air gap with the watt consumption (83 w) from the hypothesis test for the corresponding air gap. Finally, the updated sigma score and process capability analysis were performed with control charts to show the comparison after applying the DMAIC-six sigma methodology. The final sigma score was 5.1 which indicates a significant improvement of the process with the capability of saving US$23,438/year caused by the poor quality of ceiling fans.Practical implicationsOnly quantitative values of the causes behind the humming noise were possible to identify. Other trivial many causes elimination might improve the sigma score closer to 6.00. The final sigma score that was achieved from this research was sustainable.Originality/valueA structural approach with proper data analysis and application of various tools to detect the actual cause behind the humming noise of ceiling fans with numerical value has not been found in any literature. This research study can be a valuable asset for ceiling fan mass producers.
Diel differences in blue whale (Balaenoptera musculus) dive behavior increase nighttime risk of ship strikes in northern Chilean Patagonia
Authors: CARUSO Francesco , HICKMOTT Leigh , WARREN Joseph D. , SEGRE Paolo , CHIANG Gustavo , BAHAMONDE Paulina , ESPAÑOL‐JIMÉNEZ Sonia , LI Songhai , BOCCONCELLI Alessandro 
Published: November 2020

AbstractThe northern Chilean Patagonia region is a key feeding ground and a nursing habitat in the southern hemisphere for blue whales (Balaenoptera musculus). From 2014 to 2019, during 6 separate research cruises, the dive behavior of 28 individual blue whales was investigated using bio‐logging tags (DTAGs), generating ≈190 h of data. Whales dove to significantly greater depths during the day compared to nighttime (day: 32.6 ± 18.7 m; night: 6.2 ± 2.7 m; P < 0.01). During the night, most time was spent close to the surface (86% ± 9.4%; P < 0.01) and at depths of less than 12 m. From 2016 to 2019, active acoustics (scientific echosounders) were used to record prey (euphausiids) density and distribution simultaneously with whale diving data. Tagged whales appeared to perform dives relative to the vertical migration of prey during the day. The association between diurnal prey migration and shallow nighttime dive behavior suggests that blue whales are at increased risk of ship collisions during periods of darkness since the estimated maximum ship draft of vessels operating in the region is also ≈12 m. In recent decades, northern Chilean Patagonia has seen a large increase in marine traffic due to a boom in salmon aquaculture and the passenger ship industry. Vessel strike risks for large whales are likely underestimated in this region. Results reported in this study may be valuable for policy and mitigation decisions regarding conservation of the endangered blue whale.