Traditional Performance Measures Research Articles

Pearls of wisdom for aspiring physician-scientist residency applicants and program directors.

Postgraduate physician-scientist training programs (PSTPs) enhance the experiences of physician-scientist trainees following medical school graduation. PSTPs usually span residency and fellowship training, but this varies widely by institution. Applicant competitiveness for these programs would be enhanced, and unnecessary trainee anxiety relieved, by a clear understanding of what factors define a successful PSTP matriculant. Such information would also be invaluable to PSTP directors and would allow benchmarking of their admissions processes with peer programs. We conducted a survey of PSTP directors across the US to understand the importance they placed on components of PSTP applications. Of 41 survey respondents, most were from internal medicine and pediatrics residency programs. Of all components in the application, two elements were considered very important by a majority of PSTP directors: (a) having one or more first-author publications and (b) the thesis advisor’s letter. Less weight was consistently placed on factors often considered more relevant for non-physician-scientist postgraduate applicants — such as US Medical Licensing Examination scores, awards, and leadership activities. The data presented here highlight important metrics for PSTP applicants and directors and suggest that indicators of scientific productivity and commitment to research outweigh traditional quantitative measures of medical school performance.

Economic Value Added: Acritical Reading

Abstract: It is clear how important is the measure of Economic Value-Added and preference that this measure has over traditional performance measures. This measure is based on creating value for the company, and this measure is distinguished by taking into account invested capital, whether owned or borrowed. In addition, studies have shown that the measure of Economic Value Added increases the performance of the company and the performance of the management working. This measure affects the market value of the company and its use leads to maximizing the wealth of shareholders, and like all performance measures he has supporters and has critics. One of the criticisms directed against him is that he measures performance on the short level, as he cares about results, not causes, and the most important criticism directed at him is his dependence on accounting profit in the financial statements whether these statements represent the actual performance of the company or not. Keywords: Economic Value Added, Profit Indicator, Financial Management

Organizing for permanent beta: performance measurement before vs performance monitoring after release of digital services

PurposeDue to the complexity of digital services, companies are increasingly forced to offer their services “in permanent beta”, requiring continuous fine-tuning and updating. Complexity makes it extremely difficult to predict when and where the next service disruption will occur. The authors examine what this means for performance measurement in digital service supply chains.Design/methodology/approachThe authors use a mixed-method research design that combines a longitudinal case study of a European digital TV service provider and a system dynamics simulation analysis of that service provider's digital service supply chain.FindingsWith increased levels of complexity, traditional performance measurement methods, focused on detection of software bugs before release, become fragile or futile. The authors find that monitoring the performance of the service after release, with fast mitigation when service incidents are discovered, appears to be superior. This involves organizational change when traditional methods, like quality assurance, become less important.Research limitations/implicationsThe performance of digital services needs to be monitored by combining automated data collection about the status of the service with data interpretation using human expertise. Investing in human expertise is equally important as investing in automated processes.Originality/valueThe authors draw on unique empirical data collected from a digital service provider's struggle with performance measurement of its service over a period of nine years. The authors use simulations to show the impact of complexity on staff allocation.

Hybrid Data Selection With Context and Content Features for Visual Crowdsensing

Visual crowdsensing (VCS) is becoming predominant in mobile crowdsensing, but there still exist various unique challenges, including large sizes of visual data, multidimensional requirements, and intensive processing demands. As a key research problem in VCS, data selection filters out redundant data and only retains most representative samples, which can effectively reduce the complexity and cost for VCS. In this paper, we study a phase-by-phase data selection approach, in which metadata are first used to pre-select collected photos and then only selected ones are sent to a backend server for further processing based on content features. As such, the initial selection can be completed on nearby edge servers in mobile edge computing (MEC), while more intensive content processing can be done in a remote cloud. We evaluate different initial data selection algorithms using traditional performance measures as well as adapted clustering indices as quality metrics. Moreover, we formulate an integer linear program (ILP) problem for the final data selection based on the scale-invariant feature transform (SIFT) feature. This content-based selection can complement the initial data selection based on contextual metadata. The simulation results show the differences of these selection algorithms and provide guidance on how to choose an appropriate one according to application needs.

When does “inhibition of return” occur in spatial cueing tasks? Temporally disentangling multiple cue-triggered effects using response history and conditional accuracy analyses

Abstract Research on spatial cueing has shown that uninformative cues often facilitate mean response time (RT) performance in valid- compared to invalid-cueing conditions at short cue-target stimulus-onset-asynchronies (SOAs), and robustly generate a reversed or inhibitory cueing effect at longer SOAs that is widely known as inhibition-of-return (IOR). To study the within-trial time course of the IOR and facilitation effects we employ discrete-time hazard and conditional accuracy analyses to analyze the shapes of the RT and accuracy distributions measured in two experimental tasks. Our distributional analyses show that (a) IOR is present only from ~160 ms to ~280 ms after target onset for cue-target SOAs above ~200 ms, (b) facilitation does not precede IOR, but co-occurs with it, (c) the cue-triggered motor response activation is selectively and actively inhibited before target onset, (d) the IOR effect consists of a facilitatory and an inhibitory component when compared to central cueing, (e) the addition of an extra central cue causes a temporary negative cueing effect in the conditional accuracy functions, and (f) the within-trial time course of IOR is not affected much by the task employed (detection or localization). We conclude that the traditional mean performance measures conceal crucial information on behavioral dynamics in spatial cueing paradigms.

Balanced Scorecard: The Key to Employee Well-Being the Impact of Balanced Scorecard on Employee Well-Being: The Case of State of Michigan-USA

While the organizations have started to use methods consisting of financial and non-financial measures to track progress when they realized that traditional strategic management and performance measurement methods based only on financial data were not sufficient to plan the future and to be strong in competitive environments. The balanced scorecard is one of these methods that has been widely adopted and is the most popular performance method by researchers which uses a "four perspective which is financial, customer, internal process perspective and learning growth perspectives. The main function of the learning and growth perspective is to drive the major sources of human capital, informational capital, and organizational capital in the organizations. One of the most important factors of organizational success is happy employees who make a tremendous contribution to increasing organizational performance, proven by many researchers. The objective of this study was to research the impact of the Balanced Scorecard on employees’ well-being, its theoretical frameworks and concepts, and empirical research. The survey of the study involved 27334 employees working in the State of Michigan and has been analysed by 28 of Statistical Package for Social Sciences (SPSS). The study demonstrated BSC strategies were implemented in the organization have improved organizational performance in the four financial perspectives, customer, internal process, and learning &growth perspectives. With the BSC strategy, which has been followed for 20 years, and the learning and growth perspective, the organization increases the satisfaction of its employees, while organizational commitment and job engagement come to the fore. Statistical results from employee satisfaction surveys showed that BSC increased job satisfaction by 68.30% (R square: 0.683), job engagement by 71.00% (R square: 0.710), and organizational commitment by 21.30% (R square: 0.213).

On the Impact of Treatment Restrictions for the Indigent Suffering from a Chronic Disease: The Case of Compassionate Dialysis

We analyze a congested healthcare delivery setting resulting from emergency treatment of a chronic disease on a regular basis. A prominent example of the problem of interest is congestion in the emergency room (ER) at a publicly funded safety net hospital resulting from recurrent arrivals of uninsured end-stage renal disease patients needing dialysis (a.k.a. compassionate dialysis). Unfortunately, this is the only treatment option for un/under-funded patients (e.g., undocumented immigrants) with ESRD, and it is available only when the patient’s clinical condition is deemed as life-threatening after a mandatory protocol, including an initial screening assessment in the ER as dictated and communicated by hospital administration and county policy. After the screening assessment, the so-called treatment restrictions are in place, and a certain percentage of patients are sent back home; the ER, thus, serves as a screening stage. The intention here is to control system load and, hence, overcrowding via restricting service (i.e., dialysis) for recurrent arrivals as a result of the chronic nature of the underlying disease. In order to develop a deeper understanding of potential unintended consequences, we model the problem setting as a stylized queueing network with recurrent arrivals and restricted service subject to the mandatory screening assessment in the ER. We obtain analytical expressions of fundamental quantitative metrics related to network characteristics along with more sophisticated performance measures. The performance measures of interest include both traditional and new problem-specific metrics, such as those that are indicative of deterioration in patient welfare because of rejections and treatment delays. We identify cases for which treatment restrictions alone may alleviate or lead to severe congestion and treatment delays, thereby impacting both the system operation and patient welfare. The fundamental insight we offer is centered around the finding that the impact of mandatory protocol on network characteristics as well as traditional and problem-specific performance measures is nontrivial and counterintuitive. However, impact is analytically and/or numerically quantifiable via our approach. Overall, our quantitative results demonstrate that the thinking behind the mandatory protocol is potentially naive. This is because the approach does not necessarily serve its intended purpose of controlling system-load and overcrowding.

Toward an Assessment of Quality of Life Indicators as Measures of Destination Performance

This study tests a reciprocal relationship between objective quality of life indicators and traditional destination performance measures over time. A set of 16 quality of life indicators (covering economic, social, and environmental domains) and a set of five destination performance variables of tourist arrivals and spending proxies were used to perform a canonical correlation analysis. This panel data represents observations from 105 countries during the period of 1995–2018. The findings confirmed that a reciprocal link exists between the two sets. Specifically, the results showed that economic factors, along with education, and health indicators are strongly associated with performance measures of the tourism industry. The article concludes with implications for destination managers and avenues for future research.

MEASUREMENT OF COOPERATIVE PERFORMANCE WITH THE BALANCE SCORECARD ANALYSIS APPROACH

This research aims to determine and analyze the Balance Scorecard approach as a measurement the performance of the Republic of Indonesia Employee Cooperative at “Kopertis” Region VII in Surabaya. The Balance Scorecard approach takes into account financial and non-financial aspects that are neglected by traditional performance measurements. Data collection was carried out by interview method with related sections and documentation. The data analysis technique used a qualitative descriptive method with a Balance Scorecard approach through 4 perspectives, namely a financial perspective, a customer perspective, an internal business process perspective and a learning and growth perspective. The results indicate that the measurement of cooperative performance in terms of 4 perspectives as a whole is good; this is indicated by a total score of 9 for financial, customer and learning & growth perspectives, obtaining good scores and a total score of 3 for internal business process perspectives obtaining sufficient scores. The conclusion that can be drawn is that the measurement of performance in cooperatives is more comprehensive. The suggestion proposed is the “Kopertis” Region VII Civil Servant Cooperative in measuring performance using the Balance Scorecard in order to find out the potential that the cooperative has for the welfare of all members.

A resilience engineering-based framework for assessing safety performance measurement systems: A study in the construction industry

Resilience engineering (RE) offers a complementary perspective to traditional safety performance measurement systems (SPMSs), by taking into account the complexity of socio-technical systems. However, previous studies do not make it clear how that perspective could be translated into practice, nor the utility of that analysis. In order to address this gap, this paper presents a RE-based framework for assessing SPMSs in construction projects, which includes six stages: (i) obtain an overview of the existing SPMS; (ii) understand how complexity influences safety performance, based on the complexity assessment tool known as Technical, Organizational, and Environment framework; (iii) assess the four resilience abilities (monitor, anticipate, respond, learn), based on the Resilience Assessment Grid; (iv) assess the joint evidence from the previous steps in light of RE guidelines for SPMSs; and (v) identify improvement opportunities. This framework was tested in an empirical study carried out in a Norwegian construction site, by using interviews, observations, and analysis of documents. Results pointed out examples for applying RE ideas to SPMSs as well as they shed light on how complexity may either hinder or support a SPMS.

Portfolio Upside and Downside Risk—Both Matter!

Traditional performance measures do not distinguish between <i>upside risk</i> and <i>downside risk</i>. Downside risk is based on returns that are below a target rate, below zero, below average, or below a benchmark, and vice versa for upside risk. Downside risk measures and the “duality” of beta have been discussed extensively in literature related to public markets but have not been applied to the analysis of private equity real estate in the academic literature. This article examines the measures that can distinguish between upside and downside risk that are commonly used in public markets, such as upside and downside beta and the Sortino ratio for downside analysis, and applies them to different property sectors and Core-Based Statistical Areas in the NCREIF Property Index. In addition, these measures are used to analyze gateway versus nongateway markets’ historical performance on both an upside and downside risk basis. The same techniques are applied to perform an attribution analysis of a portfolio’s alpha into upside and downside components. <b>Key Findings</b> ▪ The authors show that downside risk measures such as the Sortino ratio and downside beta can provide insights into what drives returns for different property sectors and Core-Based Statistical Areas, as well as gateway versus nongateway markets. ▪ Using the upside to downside beta ratio, the authors show how property sectors and markets vary as to whether beta is magnifying return on the upside and/or minimizing declines on the downside. ▪ By using the duality of beta, the authors show how to decompose the risk-adjusted overperformance or underperformance into upside and downside alpha earned by a portfolio, a complement to traditional Brinson attribution analysis.

Ecohydrological modelling in a deciduous boreal forest: Model evaluation for application in non‐stationary climates

AbstractSoil moisture is an important driver of growth in boreal Alaska, but estimating soil hydraulic parameters can be challenging in this data‐sparse region. Parameter estimation is further complicated in regions with rapidly warming climate, where there is a need to minimize model error dependence on interannual climate variations. To better identify soil hydraulic parameters and quantify energy and water balance and soil moisture dynamics, we applied the physically based, one‐dimensional ecohydrological Simultaneous Heat and Water (SHAW) model, loosely coupled with the Geophysical Institute of Permafrost Laboratory (GIPL) model, to an upland deciduous forest stand in interior Alaska over a 13‐year period. Using a Generalized Likelihood Uncertainty Estimation parameterisation, SHAW reproduced interannual and vertical spatial variability of soil moisture during a five‐year validation period quite well, with root mean squared error (RMSE) of volumetric water content at 0.5 m as low as 0.020 cm3/cm3. Many parameter sets reproduced reasonable soil moisture dynamics, suggesting considerable equifinality. Model performance generally declined in the eight‐year validation period, indicating some overfitting and demonstrating the importance of interannual variability in model evaluation. We compared the performance of parameter sets selected based on traditional performance measures such as the RMSE that minimize error in soil moisture simulation, with one that is designed to minimize the dependence of model error on interannual climate variability using a new diagnostic approach we call CSMP, which stands for Climate Sensitivity of Model Performance. Use of the CSMP approach moderately decreases traditional model performance but may be more suitable for climate change applications, for which it is important that model error is independent from climate variability. These findings illustrate (1) that the SHAW model, coupled with GIPL, can adequately simulate soil moisture dynamics in this boreal deciduous region, (2) the importance of interannual variability in model parameterisation, and (3) a novel objective function for parameter selection to improve applicability in non‐stationary climates.

Implementation of the diffusion model on dot-probe task performance in children with behavioral inhibition.

Attentional bias to threat, the process of preferentially attending to potentially threatening environmental stimuli over neutral stimuli, is positively associated with behavioral inhibition (BI) and trait anxiety. However, the most used measure of attentional bias to threat, the dot-probe task, has been criticized for demonstrating poor reliability. The present study aimed to assess whether utilizing a sequential sampling model to describe performance could detect adequate test-retest reliability for the dot-probe task, demonstrate stronger cueing effects, and improve the association with neural signals of early attention. One hundred and twenty children aged 9-12years completed the dot-probe task twice. During the second administration, event-related potentials (ERPs) were obtained as time-sensitive neural markers of attention. BI was not associated with traditional or diffusion model measures of performance. Traditional and diffusion model measures of performance were also not associated with N1, P2, or N2 ERP amplitude. There were main effects of Visit, in which RTs were faster and standard deviation of RT smaller during the second administration due to an increase in drift rate and a decrease in non-decision time. The traditional RT bias score (r = 0.06) and bias scores formed via diffusion model parameters (all r's < 0.40) all demonstrated poor reliability. Results confirm recommendations to move away from using the dot-probe task as the primary or sole index of attentional bias.

A critical evaluation of current definitions of necrotizing enterocolitis.

Necrotizing enterocolitis (NEC) is a devastating intestinal disease of premature infants, with significant mortality and long-term morbidity among survivors. Multiple NEC definitions exist, but no formal head-to-head evaluation has been performed. We hypothesized that contemporary definitions would perform better in evaluation metrics than Bell's and range features would be more frequently identified as important than yes/no features. Two hundred and nineteen patients from the University of Iowa hospital with NEC, intestinal perforation, or NEC concern were identified from a 10-year retrospective cohort. NEC presence was confirmed by a blinded investigator. Evaluation metrics were calculated using statistics and six supervised machine learning classifiers for current NEC definitions. Feature importance evaluation was performed on each decision tree classifier. Newer definitions outperformed Bell's staging using both standard statistics and most machine learning classifiers. The decision tree classifier had the highest overall machine learning scores, which resulted in Non-Bell definitions having high sensitivity (0.826, INC) and specificity (0.969, ST), while Modified Bell (IIA+) had reasonable sensitivity (0.783), but poor specificity (0.531). Feature importance evaluation identified nine criteria as important for diagnosis. This preliminary study suggests that Non-Bell NEC definitions may be better at diagnosing NEC and calls for further examination of definitions and important criteria. This article is the first formal head-to-head evaluation of current available definitions of NEC. Non-Bell NEC definitions may be more effective in identifying NEC based on findings from traditional measures of diagnostic performance and machine learning techniques. Nine features were identified as important for diagnosis from the definitions evaluated within the decision tree when performing supervised classification machine learning. This article serves as a preliminary study to formally evaluate the definitions of NEC utilized and should be expounded upon with a larger and more diverse patient cohort.

Firms’ performance during the COVID-19 outbreak: international evidence from 13 countries

PurposeThe purpose of this paper is to explore the impact of firm-, finance- and country-specific indicators to the performance of companies under the COVID-19 outbreak.Design/methodology/approachThe study uses a regression performance model for enterprises during the COVID-19 crisis. The investigation is based upon a data set of 5,730 firms from 13 countries collected by the World Bank through enterprise surveys. The author combined the analysis of traditional performance measurements with the testing of relatively novel variables.FindingsThis study confirms the significance of multiple factors for company performance: sector, size, participation in exports and market demand for firms’ products. Robust financing solutions during the coronavirus pandemic period include equity contributions, followed by firms’ cash balances and debt. Support by a government, however, has not yet been confirmed as a significant source of finance. This paper also suggests the importance of country-specific factors for the performance of enterprises, including the level of economic development and the corporate governance infrastructure.Practical implicationsThe research outcomes might assist regulatory bodies, policymakers and companies in their formulation of public and corporate governance strategies concerning future emergency preparedness and responses.Originality/valueThis paper is among the first empirical studies in the management realm that addresses the impact of COVID-19 on company performance, with cross-national empirical data.

How Company Size Bias in ESG Scores Impacts the Small Cap Investor

The rising popularity of socially responsible investing (SRI) has increased interest in the relationship between traditional measures of corporate financial performance (CFP) and the emerging field of corporate social performance (CSP). SRI investors have tended to have a large capitalization (cap) stock focus that has served them well in the past, but that may be suboptimal in the future if we return to a period of small cap outperformance. Using environmental, social, and governance (ESG) scores as a proxy for CSP, our research supports past studies showing a large cap bias in measures of CSP. Narrowing our focus, we find that within the US small cap stock universe, the correlation between firm size and ESG scores is greatly reduced. We construct small cap ESG leaders and laggards portfolios and test their performance. We demonstrate that performance was not affected by neutralizing these portfolios with respect to firm size. Our results reinforce the idea that CSP proxies such as ESG scores have the potential to practically enhance portfolio performance in US small cap stocks. <b>TOPICS:</b>ESG investing, analysis of individual factors/risk premia, portfolio construction, performance measurement <b>Key Findings</b> ▪ ESG size bias is not as significant in US small cap stocks as it is in US large cap stocks. ▪ Stocks with high (low) ESG scores outperform (underperform) the market in the US small cap space. ▪ It is possible for US small cap portfolio managers to use ESG as an alpha generating tool without taking size risk.

Pengaruh CSR, EVA, Dan Traditional Performance Measurement Terhadap Stock Price

The purpose of this study is to empirically examine the impact of Corporate Social Responsibility, Economic Value Added, and Traditional Performance Measurement to stock price in manufacturing companies listed on Indonesia Stock Exchange for 2016-2018 period. Samples were selected using purposive sampling method, with the amount of 73 companies resulted. Data used were financial information from financial statements and annual reports, which were processed using Eviews Ver. 11.0 program. The result of this study shows that Corporate Social Responsibility and Economic Value Added partially has positive and significant impact on stock price, while Traditional Performance Measurement have no significant impact on stock price.

TÜRKİYE ALTERNATİF PERFORMANS ÖLÇÜTLERİ REHBERİ VE BİR UYGULAMA

Geleneksel performans ölçütleri; paydaş taleplerinin değişmesi, daha fazla bilgi talebi gibi muhtelif sebeplerden dolayı zamanla yetersiz kalmıştır. Bu boşluğu alternatif performans ölçütleri olarak ifade edilen ölçütler doldurmuştur. ESMA, IOSCO, IFAC ve SEC gibi kuruluşlar son yıllarda alternatif performans ölçütleri konusunda yasal düzenlemeler oluşturmuşlar ve işletmelerin kullanımına sunmuşlardır. Türkiye’de de işletmeler alternatif performans ölçütü ifadesi kullanmadan bu kapsamda yer alan performans ölçütlerini faaliyet raporları ve yatırımcı sunumları başta olmak üzere muhtelif yerlerde kullanmaktadırlar. Uluslararası kurumların alternatif performans ölçütleri konusunda getirdiği yasal düzenlemeler ile birlikte sağlanan doğrulanabilirlik, tarafsızlık, tutarlılık ve şeffaflık ise henüz Türkiye’deki işletmeler için geçerli değildir. Bunun nedeni ise ölçütler konusunda herhangi bir düzenlemenin ulusal düzeyde yer almamasıdır. Bu alandaki boşluğun UFRS’lerin Türkiye’deki uygulaması gibi alternatif performans ölçütlerinin de uluslararası düzenlemelere paralel ulusal bir düzenleme ile giderilebileceği düşünülmektedir. Bu çalışmada, ulusal düzeydeki bu açıktan hareket edilmiş ve Türkiye için alternatif performans ölçütleri için bir ulusal rehber önerisi ve bir uygulama örneği sunulmuştur. Türkiye Alternatif Performans Ölçütleri Rehberi’nin gelecekte Türkiye’de konu hakkında yapılacak olan çalışmalara temel teşkil etmesi amaçlanmaktadır. Rehberde yer alan ve işletme paydaşlarına asgari düzeyde güvence sağlayan alternatif performans ölçütlerine ilişkin denetim kontrol listesinin ise uluslararası literatüre katkı sunması beklenmektedir.

Changes in Neuromuscular Status Across a Season of Professional Men's Ice Hockey.

Gannon, EA, Higham, DG, Gardner, BW, Nan, N, Zhao, J, and Bisson, LJ. Changes in neuromuscular status across a season of professional men's ice hockey. J Strength Cond Res 35(5): 1338-1344, 2021-To quantify changes in neuromuscular function over a full professional men's ice hockey season, 27 players (n = 18 forwards and 9 defensemen) performed 3 countermovement jumps (CMJ) each week over 30 sessions separated into 4 phases: preseason, early-season, midseason, and late-season. Outcome variables represented jump performance (jump height), kinematics (mean velocity and peak velocity), and movement strategy (countermovement depth). Mixed models characterized relationships between positional group, season phase, and CMJ outcomes. Statistical significance was set at p ≤ 0.05. Concentric peak velocity (p = 0.02), jump height (p = 0.001), and countermovement depth (p < 0.001) displayed a significant reduction across the season. Peak velocity was lower during the early-season than the preseason (-0.10 ± 0.06 m·s-1, mean change ± 95% confidence limit, p = 0.05). Countermovement depth was reduced during the early-season (-0.06 ± 0.03 m, p = 0.02), midseason (-0.10 ± 0.04 m, p = 0.002), and late-season (-0.15 ± 0.04 m, p < 0.001) relative to the preseason. Reductions in CMJ variables from preseason to in-season ranged from trivial to large. Changes in countermovement depth differed for forwards and defensemen by the season phase (p = 0.04). A professional ice hockey season decreases CMJ performance, with the effects of fatigue most prominent during the late-season phase. Countermovement depth was most sensitive to fatigue and differentiated positional-group responses. Frequent CMJ testing is useful for identifying the neuromuscular status of team-sport athletes relative to season-specific phases. Fatigue monitoring should incorporate movement-strategy variables alongside traditional measures of performance and kinematics.

The impact of dynamic capabilities and dynamic performance measurement on competitive performance: evidence from Thai hotel entrepreneurs

This research aims to provide empirical evidence on the causal relationships among the effects of dynamic capabilities and the dynamic performance measurement on high performance organizations (HPOs) and the competitive performance of hotel businesses in a world-class tourism destination of Thailand. The research using questionnaires to collect data from 115 hotel businesses located at a world class tourism destination in Thailand. The data were first analysed using descriptive statistics and then confirmatory factor analysis and structural equation modelling were conducted. The study results reveal that the causal relationship model fit the empirical data ( 2 = 74.39, p-value = 0.15, 2/df = 1.18, CFI = 0.99, GFI = 0.92, NFI = 0.96, RMSEA = 0.04, and SRMR = 0.03). In addition, the results also indicate that the dynamic capabilities have a direct positive effect on dynamic performance measurement. The study reflects that being a HPO not only has a direct positive effect on competitive performance but is also a complete mediator in transferring the effects of the dynamic capabilities and dynamic performance measurement to competitive performance. Under an increasingly dynamic environment, traditional performance measurement innovations that only consider measurement and management tend to lead to imperfections and lower benefits. Additionally, traditional performance measurements are static characteristics; therefore, it is essential to catch up with the dynamic environment. This research will provide empirical evidence of the causal relationship of how dynamic capabilities and dynamic performance measurement affect a HPO and competitive performance towards excellence under a dynamic environment.