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The purpose of this paper is to be the first empirical article to provide necessary standard deviation inputs for adoption in probabilistic prognostications of hotel revenues and expenses, i.e. prognostications that consider risk. Commonly accepted methodologies to develop hotel financial projections resulting in point estimates of upcoming performance have been perceived as egregiously insufficient because they do not consider risk in lodging investments. Previous research has recommended the use of probabilistic methodologies to address this concern, and it has been recommended that analysts use Monte Carlo simulation. This methodology requires the estimation of standard deviations of specific, future hotel revenue and expense items, and this paper provides such inputs based on a large sample of actual, recent data.

This study provides actual standard deviations using a sample of recent hotel profit and loss (P&L) statements for over 3,000 hotels (Over 19,000 P&L statements) to provide analysts with empirically-supported standard deviations that may be applied to Uniform System of Accounts for the Lodging Industry (USALI) hotel revenues and expenses in hotel financial (revenue and expense) prognostications.

Findings are presented for standard deviations based on typical line items as defined in the USALI, and these findings may be used by practitioners as inputs for hotel financial projections. Findings also include that hotel revenue items generally have higher standard deviations than expense items. Findings are presented in detail in the manuscript, including overall findings, as well as findings based on hotel class.

Rather than practitioners adopting standard deviations of hotel revenue and expense line items based on guesswork or judgment, which is the current “state of the art” in hotel financial projections, this paper provides practitioners with actual standard deviations which may be adopted in probabilistic prognostications of hotel revenues and expenses.

This paper may be the first to provide practitioners with actual standard deviations, based on typical USALI line items, for adoption in probabilistic prognostications of hotel revenues and expenses.

An S-curve is an essential project-management tool. However, it is difficult to adjust S-curve to deal with a force majeure event. The present study develops four valuable adjustment approaches, designed to achieve a compromise between the views of the client and contractor. These can be used to control projects after a force majeure event.

The present study develops four adjustment approaches, which can be used to achieve a compromise between the views of the client and those of the contractor when controlling projects after a force majeure. To determine the S-curves during a force majeure event, two approaches can be selected: BCWS (budgeted cost of scheduled work)-base approach, or BCWP (budgeted cost of work performed)-base approach. To determine the rest of S-curves after a force majeure event, two approaches can be considered: maintaining the original curve of the remaining BCWS, or allocating the original curve of the remaining BCWS. Based on the validation of three empirical cases, drawn from a professional project-management website, this study confirms the feasibility of four proposed empirical approaches and a selection procedure for S-curve adjustment.

The S-curve-adjustment approaches presented here can be used to deal with cases that are ahead of, on and behind schedule. Using the proposed approaches and selection procedure, contractors can easily revise S-curves and control projects more effectively. To deal with a force majeure event, such as COVID-19, they are strongly advised to adopt the approaches labeled SA-A1 (to adjust the S-curve based on the extension ratio multiplied by the difference in progress during the force majeure) and SA-B1 (to maintain the original curve of the remaining BCWS) for the A/E and E/F curves, respectively.

The proposed approaches can be used in cases of continuous construction during force majeure events. If construction work is totally suspended during such an event, it will be necessary to fine-tune the proposed approaches.

Previous studies have used case-oriented or mathematical-simulation approaches to forecast S-curves. The present study proposes simple approaches that allow the client and contractor to adjust the S-curve easily after a force majeure event. These approaches can be used to adjust work and project-completion targets within an extended duration. Selecting the right S-curve adjustment approach can help to control the remainder of the project, reducing the possibility of delay claims.

Online ride-hailing platforms match drivers with passengers by receiving ride requests from passengers and forwarding them to the nearest driver. In this context, the low acceptance rate of offers by drivers leads to friction in the process of driver and passenger matching. What policies by the platform may increase the acceptance rate and by how much? What factors influence drivers' decisions to accept or reject offers and how much? Are drivers more likely to turn down a ride offer because they know that by rejecting it, they can quickly receive another offer, or do they reject offers due to the availability of outside options? This paper aims to answer such questions using a novel dataset from Tapsi, a ride-hailing platform located in Iran.

The authors specify a structural discrete dynamic programming model to evaluate how drivers decide whether to accept or reject a ride offer. Using this model, the authors quantitatively measure the effect of different policies that increase the acceptance rate. In this model, drivers compare the value of each ride offer with the value of outside options and the value of waiting for better offers before making a decision. The authors use the simulated method of moments (SMM) method to match the dynamic model with the data from Tapsi and estimate the model's parameters.

The authors find that the low driver acceptance rate is mainly due to the availability of a variety of outside options. Therefore, even hiding information from or imposing fines on drivers who reject ride offers cannot motivate drivers to accept more offers and does not affect drivers' welfare by a large amount. The results show that by hiding the information, the average acceptance rate increases by about 1.81 percentage point; while, it is 4.5 percentage points if there were no outside options. Moreover, results show that the imposition of a 10-min delay penalty increases acceptance rate by only 0.07 percentage points.

To answer the questions of the paper, the authors use a novel and new dataset from a ride-hailing company, Tapsi, located in a Middle East country, Iran and specify a structural discrete dynamic programming model to evaluate how drivers decide whether to accept or reject a ride offer. Using this model, the authors quantitatively measure the effect of different policies that could potentially increase the acceptance rate.

Accurate presentation of the rock microstructure is critical to the grain-scale analysis of rock deformation and failure in numerical modelling. 3D granite microstructure modelling has only been used in limited studies with the mineral pattern often remaining poorly constructed. In this study, the authors developed a new approach for generating 2D and 3D granite microstructure models from a 2D image by combining a heterogeneous material reconstruction method (simulated annealing method) with Voronoi tessellation.

More specifically, the stochastic information in the 2D image is first extracted using the two-point correlation function (TPCF). Then an initial 2D or 3D Voronoi diagram with a random distribution of the minerals is generated and optimised using a simulated annealing method until the corresponding TPCF is consistent with that in the 2D image. The generated microstructure model accurately inherits the stochastic information (e.g. volume fraction and mineral pattern) from the 2D image. Lastly, the authors compared the topological characteristics and mechanical properties of the 2D and 3D reconstructed microstructure models with the model obtained by direct mapping from the 2D image of a real rock sample.

The good agreements between the mapped and reconstructed models indicate the accuracy of the reconstructed microstructure models on topological characteristics and mechanical properties.

The newly developed reconstruction method successfully transfers the mineral pattern from a granite sample into the 2D and 3D Voronoi-based microstructure models ready for use in grain-scale modelling.

This study aims to explore how subsidiary capabilities collectively configure for performance. Additionally, it seeks to examine whether these configurations of capabilities can provide equifinal solutions through developing a comprehensive research framework that focuses on subsidiaries in China.

With a data set collected through a questionnaire from 172 Korean multinational enterprises (MNEs) in China, this study used a fuzzy-set qualitative comparative analysis to detect the capability conditions and configurations. These configurations represent combinations of various subsidiary capabilities linked to high performance.

This study identified several complex pathways with distinct configurations for high subsidiary performance. The findings demonstrate the importance of configurations over individual conditions. Thus, the results highlight that the effectiveness of diverse capabilities, which are widely believed to singularly contribute to the high performance of MNE subsidiaries, depends on how each combines with other capabilities. Overall, the findings provide a richer and fine-grained understanding of the role and relative importance of various forms of MNE subsidiary capabilities and how the joint effect of these subsidiaries contributes to high performance.

This study suggests that MNE managers should comprehensively understand how subsidiary capabilities are configured to produce subsidiary performance outcomes. This specifically illustrates the importance of understanding the mutually conflicting yet collectively exhaustive results of multi-selective solutions and aims to align with China’s industrial and regional heterogeneity.

By examining the role of MNE subsidiary capability configurations, which may collectively influence the subsidiary’s performance, this study contributes to the literature. It elucidates how MNE subsidiaries may achieve superior performance by developing and possessing various capabilities tailored to the local context.

This study aims to examine the applicability of Hartmann et al.’s (2018) service ecosystem framework to the day-to-day management of the modern sales force. The authors provide a review of the framework, acknowledging its strengths, while also indicating areas for advancement. The authors conclude with recommendations to the framework and indicate opportunities where future research could advance sales theory.

A review of the theoretical underpinnings of the service ecosystem framework is weighed against the established roles and responsibilities of the modern sales force in the literature.

The ability of the framework to capture the multi-level, multi-actor and dynamic aspects of sales represents an improvement in the conceptualization of selling is critical. Suggestions around the refinement for meso-level sales interactions and a more pliant application of service dominant-logic are offered.

The suggested extensions of the framework continue the advancement of novel theorization for the field of sales. Priorities for future research include consideration of ethical implications of the framework and formulations of new management strategies reflective of the broad and dynamic properties of the ecosystem conceptualization.

This paper provides managerial guidelines and implications tied specifically to the thick and thin crossing points and how they may impact employee decision-making.

To the best of the authors’ knowledge, this study is the first to pointedly examine the service ecosystem framework with respect to established principles of managing a modern sales force.

This paper addresses the growing fragmentation between traditional and digital service innovation (DSI) research and offers a unifying metatheoretical framework.

Grounded in service-dominant (S-D) logic's service ecosystems perspective, this study builds on an institutional and systemic, rather than product-centric and linear, conceptualization of value creation to offer a unifying framework for (digital) service innovation that applies to both physical and digital service provisions.

This paper questions the commonly perpetuated idea that DSI fundamentally changes the nature of innovation. Instead, it highlights resource liquification—the decoupling of information from the technologies that store, transmit, or process this information—as a distinguishing characteristic of DSI. Liquification, however, does not affect the relational and institutional nature of service innovation, which is always characterized by (1) the emergence of novel outcomes, (2) distributed governance and (3) symbiotic design. Instead, liquification makes these three characteristics more salient.

In presenting a cohesive service innovation framework, this study underscores that all innovation processes are rooted in combinatorial evolution. Here, service-providing actors (re)combine technologies (or more generally, institutions) to adapt their value cocreation practices. This research demonstrates that such (re)combinations exhibit emergence, distributed governance and symbiotic design. While these characteristics may initially seem novel and unique to DSI, it reveals that their fundamental mechanisms are not limited to digital service ecosystems. They are, in fact, integral to service innovation across virtual, physical and blended contexts. The study highlights the importance of exercising caution in assuming that the emergence of novel technologies, including digital technologies, necessitates a concurrent rethinking of the fundamental processes of service innovation.

The overall goal of science is to build a valid and reliable body of knowledge about the functioning of the world and how applying that knowledge can change it. As personnel and human resources management researchers, we aim to contribute to the respective bodies of knowledge to provide both employers and employees with a workable foundation to help with those problems they are confronted with. However, what research on research has consistently demonstrated is that the scientific endeavor possesses existential issues including a substantial lack of (a) solid theory, (b) replicability, (c) reproducibility, (d) proper and generalizable samples, (e) sufficient quality control (i.e., peer review), (f) robust and trustworthy statistical results, (g) availability of research, and (h) sufficient practical implications. In this chapter, we first sing a song of sorrow regarding the current state of the social sciences in general and personnel and human resources management specifically. Then, we investigate potential grievances that might have led to it (i.e., questionable research practices, misplaced incentives), only to end with a verse of hope by outlining an avenue for betterment (i.e., open science and policy changes at multiple levels).

This paper aims to explore the topic of adaptive reuse referring to urban open spaces into a more-than-human perspective. It underlines that dealing with heritage means being part of an inherent and ongoing process of transformation and so that reuse is inextricably an adaptive practice, constantly facing mutations, and that adaptation is a coral practice that involves different kinds of users and makers, inclusive of human and not human livings.

This paper looks at the lexicon of abandonment, in search of the more essential and intense meanings of words, and at some pioneering practices in Europe to comprehend the aesthetic and ethical implications of adaptive reuse of neglected landscapes.

Processes of reuse involve many different communities of users who in turn continuously redesign the site, into a comprehensive, coral and conflicting collaboration, whose results are never given once for all and are both uncanny and beautiful, scaring and marvellous, like a monster.

Accepting the idea that humans are not the only users and makers of urban sites can widen the range of tools, methods and values involved in heritage adaptive reuse.

This paper tries to widen the meanings of adaptation into a multispecies perspective. It intends to broaden the range of agents that can be involved as users and makers, assuming a more-than-human point of view that is not yet commonly applied.