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Gillette’s historically successful “razor and blade” business model (RBM) has been a promising benchmark for multiple businesses across diverse industries worldwide in the past several decades. The extant literature deals with very few nuances of this business model notwithstanding the fact that there are several variants of this business model being put to practical use by firms in diverse industries in grossly metaphorically equivalent situations.

This study adopts the 2 × 2 truth table framework from the domains of mathematical logic and combinatorics in fleshing out all possible (four logical possibilities) variants of the razor and blade business model for further analysis. This application presents four mutually exclusive yet collectively exhaustive possibilities on any chosen dimension. Two major dimensions (viz., provision of subsidy and intra- or extra-firm involvement in the making of razors or blades or both) form part of the discussion in this paper. In addition, this study synthesizes and streamlines entrepreneurial wisdom from multiple intra-industry and inter-industry benchmarks in terms of real-time firms explicitly or implicitly adopting several variants of the RBM that suit their unique context and idiosyncratic trajectory of evolution in situations that are grossly reflective of the metaphorically equivalent scenario of razor and recurrent blades. Inductive method of research is carried out with real-time cases from diverse industries with a pivotally common pattern of razor and blade model in some form or the other.

Several new variants of the razor and blade model (much beyond what the extant literature explicitly projects) have been discovered from the multiple metaphorically equivalent cases of RBM across industries. All of these expand the portfolio of options that relevant entrepreneurial firms can explore and exploit the best possible option chosen from them, given their unique context and idiosyncratic trajectory of growth.

This study has enriched the literature by presenting and analyzing a more inclusive or perhaps comprehensive palette of explicit choices in the form of several variants of the RBM for the relevant entrepreneurial firms to choose from. Future research can undertake the task of comparing these variants of RBM with those of upcoming servitization business models such as guaranteed availability, subscription and performance-based contracting and exploring the prospects of diverse combinations.

Smart entrepreneurial firms identify and adopt inspiring benchmarks (like razor and blade model whenever appropriate) duly tweaked and blended into a gestalt benchmark for optimal profits and attractive market shares. They target diverse market segments for tied-goods with different variants or combinations of the relevant benchmarks in the form of variegated customer value propositions (CVPs) that have unique and enticing appeal to the respective market segments.

Value-sensitive customers on the rise globally choose the option that best suits them from among multiple alternatives offered by competing firms in the market. As long as the ratio of utility to price of such an offer is among the highest, even a no-frills CVP may be most appealing to one market segment while a plush CVP may be tempting to yet another market segment simultaneously. While professional business firms embrace resource leverage practices consciously, amateur customers do so subconsciously. Each party subliminally desires to have the maximum bang-to-buck ratio as the optimal return on investment, given their priorities ceteris paribus.

Prior studies on the RBM have explicitly captured only a few variants of the razor and blade model. This study is perhaps the first of its kind that ferrets out many other variants (more than ten) of the razor and blade model with due simplification and exemplification, justification and demystification.

This paper aims to examine whether firms meeting or just beating an earnings benchmark engage in tone management in earnings conference calls to complement earnings management in the UK context. It also investigates whether the audience tone in beating or just meeting earnings fails to predict future performance.

This study was performed using a sample of non-financial UK firms listed in the FTSE 350 index over the period 2010–2015.

The findings show that firms that exercise more earnings management to meet or just beat earnings are positively associated with the abnormal tone during earnings conference calls. The outcomes also reveal that the audience’s tone of firms meeting or just beating an earnings benchmark fails to predict future performance. This confirms the effectiveness of the tone management in managing the perception of audience.

This study highlights the need for increased accountability by firms on earnings conference call. It also supports academics and practitioners in understanding the management discretion used in reporting and communication during the earnings conference call. Overall, the results of this study are beneficial for regulators, policymakers and professionals, regarding confirming the need for the earnings conference calls to be regulated.

To the best of the authors’ knowledge, this is the first study that examines the association between earnings management and tone management in the UK earnings conference calls. It adds to the existing literature by examining the self-serving behaviour of managerial tone during earnings conference calls within a sitting in which meeting or just beating a benchmark is used. Unlike several studies that explain the behaviour of tone as a signalling strategy, this study reveals that the tendency of impression management behaviour can explain the tone management.

Carbon emissions commonly serve as an indicator for environmental friendliness, and so more and more carbon emission calculators (CECs) are offered that allow an estimation of the environmental footprint of freight transport operations. Unfortunately, their exact measurement is challenging due to the availability or poor quality of necessary input data and a multitude of possible calculation methods that may result in highly inaccurate to very misleading figures.

A structured online search was conducted to identify suitable online carbon emission calculators (OCECs) for further assessment in the form of a benchmark case that includes different modes of transport from road and rail to air and sea between China and Europe. Further comparison resulted in a ranking of OCECs along the categories of transparency (routing system, data sources and calculation method), completeness (input options) and accuracy (data output).

Different predefined inputs and calculation methods employed by the OCECs assessed inevitably result in a wide spread of more or less reliable carbon footprint measurement results.

All potential users of CECs, including policymakers, actors from the transport industry and other stakeholders, are well advised to question greenhouse gas (GHG) emission statements that are not backed by transparent procedures and internationally recognized calculation standards.

This study, including a benchmark case and a ranking, offers a guideline for potential users of CEC to avoid major pitfalls coming along with the present carbon footprint measurement of freight transport operations.

This paper studies the relationship between CEO pay-performance sensitivity and CEO pay for luck as well as the asymmetric benchmarking of CEO pay in which good luck is rewarded but bad luck is not penalized symmetrically. We further explore the impact of the regulatory changes on executive compensation taking effect in the 2000s on CEO pay for luck and asymmetry.

In this study, we examine the relationship between CEO pay-performance sensitivity and CEO pay for luck and the asymmetric benchmarking of CEO compensation. The sample consists of DJIA component companies over a 71-year period from 1950 to 2020. CEO pay-performance sensitivity is measured by both delta and Jensen-Murphy pay-performance sensitivity.

We find that an increase in CEO pay-performance sensitivity as measured by both delta and Jensen-Murphy pay-performance sensitivity leads to an increase in the degree of CEO pay for luck but tends to reduce the level of CEO pay for luck asymmetry. In addition, we find that the major pay-related regulatory changes in recent years have mitigated the degree of CEO pay for luck and pay asymmetry, in which CEO pay structure and the associated CEO pay-performance sensitivity are major mechanisms through which the regulatory changes take effect.

Our findings provide empirical evidence supporting the argument that both optimal contracting and rent extraction should be considered as important determinants of CEO compensation.

When a firm designs the pay packages for its CEO to align CEO wealth to firm performance, CEO pay-performance sensitivity is expected to improve. However, the improved CEO PPS can also lead to an increased CEO pay for non-performance (Luck), which is an undesired outcome from the shareholder view. Therefore, a firm should thoroughly consider various advantages and disadvantages when compensating its top executives. Third, pay-related regulations have indeed achieved some intended outcomes such as the diminished pay for luck and asymmetry, but they also exacerbated the positive relationship between CEO pay-performance sensitivity and the asymmetric benchmarking of CEO pay. It seems that executive pay-related regulations cannot achieve perfect outcomes without side effects. Continuous reforms and regulations on corporate governance should be a dynamic process under various changing situations.

This study contributes to the literature on executive pay for luck and asymmetry in several ways. First, our study is among the few studies empirically testing the relationship between CEO pay-performance sensitivity and pay for luck and asymmetry. We find that CEO pay-performance sensitivity tends to increase the degree of CEO pay for luck but reduce the level of asymmetric benchmarking of CEO pay. These findings partly support the rent extraction theory grounded on the managerial power hypothesis and partly support the optimal contracting theory. Our findings confirm that the optimal contracting theory and the rent extraction theory are both important for explaining the practices and historical trends of CEO compensation.

The purpose of this paper is to describe sustainability of hollow and solid blocks in sub-Saharan Africa.

Indicators of stakeholder value are proposed for measuring block sustainability based on comparisons of user building value price and carbon emissions. Block manufacturing processes in Tanzania and Uganda are described and assessed in this context.

The results from Uganda indicate that there are economic and environmental advantages in using hollow blocks as long as they are produced to statutory compliance levels. However, where blocks are not produced to standard requirements, the results indicate that it is better to use solid blocks. This surprising result seems to indicate that blocks prepared using low additions of cement might have sufficient functional quality for simple residential building applications even though they might not meet current standard strength requirements and have low cement productivity. These results also indicate that the improvement potential indicated previously cannot be realised when hollow blocks are used for simple construction needs.

Clear benchmarks for the best practical level of cement block sustainability seem to be missing. The first reasons is that the lowest acceptable compressive strength has not been defined since standard requirements might not be relevant in the studied context. The second one is that the lowest possible practically achievable cement content with acceptable cement productivity has not been established.

Understanding sustainability can be very difficult and substantial work needs to be done to introduce operational sustainability indicators.

The results contribute to the discussion of understanding, defining and measuring sustainability.

To assess patient safety culture in a teaching hospital in Jordan, identify the demographic and professional characteristics that impact safety culture, and benchmark patient safety culture with similar studies in the region.

A cross-sectional design was applied. Responses were analyzed using SPSS software. Descriptive and inferential statistics were used to analyze the data.

In total, 430 (80.5%) participants were nurses and physicians; 300 (56.20%) were females; 270 (50.6%) were in the age group 25–34 years of age. Participants provided the highest positive ratings for “teamwork within units” (60.7%). On the contrary, participants recorded a low positive reaction to the proposition that the response to error was punitive in nature. Of the participants, about 53% did not report any events in the past year.

The average positive response of PSC composites varied from 28.2 to 60.7%. Therefore, patient safety culture in this Jordanian hospital was revealed fragile. This research informs and enables managers and policymakers to plan for future interventions to improve patient safety culture in healthcare institutions.

Long-term forecasts about commodity market indicators play an important role in informing policy and investment decisions by governments and market participants. Our study examines whether the accuracy of the multi-step forecasts can be improved using deep learning methods.

We first formulate a supervised learning problem and set benchmarks for forecast accuracy using traditional econometric models. We then train a set of deep neural networks and measure their performance against the benchmark.

We find that while the United States Department of Agriculture (USDA) baseline projections perform better for shorter forecast horizons, the performance of the deep neural networks improves for longer horizons. The findings may inform future revisions of the forecasting process.

This study demonstrates an application of deep learning methods to multi-horizon forecasts of agri-cultural commodities, which is a departure from the current methods used in producing these types of forecasts.

The recruitment of undergraduate students within English universities is of vital importance to both the academic success and the financial stability of the organisation. Despite the primacy of the task, there has been a dearth of research looking at related performance and how to ensure that the process is optimised. The purpose of this study was to investigate the degree of variation both within a university and between different universities. The reliance that individual programmes and/or universities place on the Clearing process is key; given its uncertainty, resource demands and timing shortly before students take up their places.

The Nomogramma di Gandy diagrammatical approach utilises readily available data to analyse universities’ performance in recruiting students to different programmes, and the degree to which they each rely of the Clearing process. Inter-university performance was investigated on a whole-student intake basis for a sample of English universities, representative of type and region.

The study found that there were disparate patterns for the many programmes within the pilot university and also disparate patterns between different types of universities across England. Accordingly, universities should internally benchmark their programmes to inform both strategic and tactical decision-making. Similarly, Universities and Colleges Admissions Service benchmarking inter-university patterns could inform the overall sector.

The approach and findings provide lessons for analysing student recruitment which could be critical to universities’ academic and financial health, in an increasingly competitive environment.

Patient safety is a top priority globally. A robust healthcare system requires strategic collaboration between research and development. The author analysed over 300 cases from seven hospitals using the failure modes, effects, and criticality analysis (FMECA) tool to understand the underlying causes of medical errors.

The author studied seven hospitals and 300 cases using FMECA to prioritise activities. The findings showed that high-priority events occurred less frequently but had the potential to cause the most harm. Team members evaluated independently to ensure unbiased evaluations. This approach is useful for setting priorities or assessing difficulties.

Poor communication and lack of coordination among staff in a healthcare organisation caused misunderstandings, ineffective decision-making, delays in patient care, and medical errors. Implementation of effective communication and coordination protocols can help avoid these problems.

The study recommends using FMECA to identify and prioritise failures and conducting in-depth analyses to understand their root causes. It also highlights the importance of interdisciplinary knowledge and soft skills for healthcare staff.

This study reveals the significance of FMECA in healthcare risk management and benchmarking. FMECA helps identify system failures, develop prevention strategies, and evaluate effectiveness against industry benchmarks. It offers healthcare professionals a valuable tool to enhance patient safety and improve healthcare quality.

There is widespread concern about low adherence to clinical practice guidelines (CPGs) and the low adoption of new medical technologies. To assist the regulatory response, we propose benchmarking clinical practice on the lower bound on the probability that a recommended treatment/new technology achieves a better outcome. This inequality–probability bound can be estimated from marginal outcome distributions. We illustrate the approach by comparing Swedish cardiologists' adoption of drug-eluting stents (DESs) with the inequality–probability bound on this technology improving outcomes. A substantial fraction of cardiologists are below the benchmark.