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The authors developed and validated an algorithm using health administrative data to identify patients who are attached or uncertainly attached to a primary care provider (PCP) using patient responses to a survey conducted in Ontario, Canada.

The authors conducted a validation study using as a reference standard respondents to a community-based survey who indicated they did or did not have a PCP. The authors developed and tested health administrative algorithms against this reference standard. The authors calculated the sensitivity, specificity positive predictive value (PPV) and negative predictive value (NPV) on the final patient attachment algorithm. The authors then applied the attachment algorithm to the 2017 Ontario population.

The patient attachment algorithm had an excellent sensitivity (90.5%) and PPV (96.8%), though modest specificity (46.1%) and a low NPV (21.3%). This means that the algorithm assigned survey respondents as being attached to a PCP and when in fact they said they had a PCP, yet a significant proportion of those found to be uncertainly attached had indicated they did have a PCP. In 2017, most people in Ontario, Canada (85.4%) were attached to a PCP but 14.6% were uncertainly attached.

Administrative data for nurse practitioner's encounters and other interprofessional care providers are not currently available. The authors also cannot separately identify primary care visits conducted in walk in clinics using our health administrative data. Finally, the definition of hospital-based healthcare use did not include outpatient specialty care.

Uncertain attachment to a primary health care provider is a recurrent problem that results in inequitable access in health services delivery. Providing annual reports on uncertainly attached patients can help evaluate primary care system changes developed to improve access. This algorithm can be used by health care planners and policy makers to examine the geographic variability and time trends of the uncertainly attached population to inform the development of programs to improve primary care access.

As primary care is an essential component of a person's medical home, identifying regions or high need populations that have higher levels of uncertainly attached patients will help target programs to support their primary care access and needs. Furthermore, this approach will be useful in future research to determine the health impacts of uncertain attachment to primary care, especially in view of a growing body of the literature highlighting the importance of primary care continuity.

This patient attachment algorithm is the first to use existing health administrative data validated with responses from a patient survey. Using patient surveys alone to assess attachment levels is expensive and time consuming to complete. They can also be subject to poor response rates and recall bias. Utilizing existing health administrative data provides more accurate, timely estimates of patient attachment for everyone in the population.

The purpose of this paper is to analyse the impact of Andalusia’s tourism promotion budgets and the efficiency of its campaigns from 2010 to 2022.

A mixed-methods approach is used. Tourism promotion budgets from 2010 to 2022 were measured as a supply indicator. Demand indicators (e.g. airport’s passenger arrivals, number of tourists and hotel occupancy rate) are analysed to measure tourism promotion budget impacts on them.

Tourism promotion budgets are a priority to stimulate tourism demand for Andalusia in times of uncertainly, and promotion campaigns are pivotal to attract and convert potential customers into actual tourists. Moreover, findings reveal that tourism promotion budgets had positive impacts on tourism demand. Whereas tourism promotion campaigns such as “Andalucía wants you back”, “Intensely”, Fitur, World Travel Market, ITB Berlin events and tourism advertising through digital channels have helped to improve tourism demand in Andalusia, ignoring the effects of the COVID-19 pandemic in the year 2020.

This study emphasizes how tourism promotion budgets and promotion campaigns must be constantly monitored by destination marketing organizations to measure the efficiency and effectiveness of assigned economic budgets and its return on investment.

Purpose – The purpose of this study is to examine the effect of corporate social responsibility (CSR) on profitability in agricultural sector companies, especially the agricultural sub-sector in the Indonesia Stock Exchange (IDX). These sub-sectors are designated as one sub-plantation group with one value and another valuable sub-sector. This study uses secondary data of financial statements for the period 2015–2016 accessed on the following website: www.idx.co.id.

Design/Methodology/Approach – The data analysis method used in this research, using dummy regression method with an independent variable, is called Corporate Social Responsibility (CSR); Return on Assets (ROA), Return on Equity (ROE), and Net Profit Margin (NPM) are used as dependent variables. Besides this, this study included a sub-sector variable in agricultural sector as a dummy variable.

Findings – This study found that the ability to explain CSR is greater by the ROE on plantation companies. These findings indicate that CSR has a signal for investors when investing in capital markets.

Research Limitations/Implications – This study had restrictiveness in model that was used only profitability ratio as an independent variable. This study also used during a two-year period. Alongside that, the next study is needed to search in other sectors by entering a sector variable as a dummy variable.

Practical Implications – Implementation of CSR was a solution for company to repair organizational and financial performance. So, Properly Company Management uncertainly implement CSR on their environment.

Originality/Value – All sub-sectors in agriculture in the IDX did not have different viewpoints for the implementation of a CSR program to their environment.

Behavioral accounting research deals with a complex set of phenomenon including the broad domain of human decision making under uncertainty. Two aspects of decision making of particular relevance to accounting and auditing research are two constructs that are inexorably interrelated: uncertainty and information (evidence). This paper introduces a theoretical perspective that enriches the knowledge-set that may be used in behavioral accounting research when confronting decision contexts that involve uncertainly.

The main body of the paper is an introduction to belief functions. The introduction includes a discussion of the fundamental constructs and then illustrates the use of belief functions in two audit settings: traditional financial statement audit planning and the evaluation of evidence in a cascaded-inference setting involving the ebaluation of internal accounting control. The paper concludes with a brief exploration of some of the research issues and opportunities that are related to the potential use of belief functions in behavioral accounting research.

This study analyses interviews with Spanish students and American and British faculty in an MBA program in Spain. Predictions about cultural differences were derived from Hofstede's (1980a) study of cultural values. Cultural differences were expected primarily on dimensions of uncertainty avoidance and masculinity‐femininity. Different processes of acculturation were expected for students and for faculty, and the language of instruction (English) was expected to place an additional burden on students. Interviews showed the utility of Hofstede's concepts for understanding classroom interaction, especially pertaining to aspects of the masculinity‐femininity dimension and to the role of language. Relatively few differences were associated with the dimension of uncertainly avoidance. Also, acculturation appeared to proceed only through the early stages of cultural adaptation for students and for faculty. The discussion leads to recommendations for both longitudinal and comparative studies for understanding the role of culture in education.

The Geac 8000 Library System from Canada, installed at two sites of the Polytechnic, is based on a minicomputer offering 64K Bytes of memory for each site and 96K shared memory. The description of this fully online system using Informer Keyboard/VDUs for cataloguing and for online circulation control using attached lightpens, includes file handling, issue procedures, catalogue interrogation and the keys available for searching — class number, author, title, ISBN, ISSN, barcode, subject headings. Ways of browsing through the files starting with uncertainly spelt authors is also described in relation to the way library readers use the public terminals provided in the library. These offer limited access and do not allow unauthorised alterations to records. Lost badges and books, reservations provision, access to user data, generation of notices to readers are all described in varying detail. Reliability and precautions against failure are outlined. The procedures for restart without data loss after power failure, and the provision of portable barcode to allow continued operation of the loans system, give the necessary back up to cover most eventualities. The system will most likely be extended to include further Geac modules after a suitable period of consolidation.

This interview with the authors of Strategy – Beyond the Hockey Stick offers their insights into a major problem which has bedevilled the strategy process in too many companies over the years - the combination of bold but delusional “hockey-stick” forecasts and timid strategic moves – a coupling that severely limits the impact of any strategy.

The McKinsey authors examined publicly available information on the world’s 2,393 largest companies, and plotted their average annual economic profit

They found that the curve is extremely steep at the both ends: those in the top quintile average some 30 times as much economic profit as those in the middle three quintiles.

One of the biggest pitfalls in the strategy process is this very human propensity for bold forecasts and timid actions. Strategy requires confronting uncertainly head-on by embracing the notion of probability by calibrating the odds of a strategy succeeding, building in explicit trigger points to re-examine decisions as we learn more. 10;

What has been largely missing from the literature is a study of the average-to-top transition based on an extensive data set, one that encompasses a greater range of performance profiles and average-to-top transition trajectories. This is the knowledge gap that Strategy Beyond the Hockey Stick: People, Probabilities, and Big Moves to Beat the Odds fills.

This study aims to achieve long-term prediction on a specific monotonic data series of atmospheric corrosion rate vs time.

This paper presents a new method, used to the collected corrosion data of carbon steel provided by the China Gateway to Corrosion and Protection, that combines non-linear gray Bernoulli model (NGBM(1,1) with genetic algorithm to attain the purpose of this study.

Results of the experiments showed that the present study’s method is more accurate than other algorithms. In particular, the mean absolute percentage error (MAPE) and the root mean square error (RMSE) of the proposed method in data sets are 9.15 per cent and 1.23 µm/a, respectively. Furthermore, this study illustrates that model parameter can be used to evaluate the similarity of curve tendency between two carbon steel data sets.

Corrosion data are part of a typical small-sample data set, and these also belong to a gray system because corrosion has a clear outcome and an uncertainly occurrence mechanism. In this work, a new gray forecast model was proposed to achieve the goal of long-term prediction of carbon steel in China.