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The purpose of this paper is to critically address the key issues facing organisations in implementing knowledge management (KM) initiatives and frameworks and how to develop fit-for-purpose an integrated knowledge management framework (KMF) for organisational excellence. In doing so, the paper critically review concepts, frameworks and models of KM to introduce the SMART KM model to support the successful introduction of KM to an organisation through systematic and well-defined steps. In addition to well-founded theories, SMART KM model is also driven by best-in-class KM practices from a number of industries and sectors. SMART KM contains number of business components which supports knowledge flow throughout the organisations which can be tailored to achieve the organisation-specific goals and objectives in alignment with the adopted operating model. Throughout the paper, number of key issues facing organisations in implementing KM initiatives will be introduced and discussed. The readers would also be able to realise the design principles supporting SMART KM model and how it can be used to improve performance and achieve organisational excellence.

The paper provides an in-depth and critical review of the literature and theories on KM. In doing so, several sources have been reviewed and consulted including various mainstream referred journals focussing on KM, change management, management, HR, social science, strategy, etc. as well as books, online databases, governmental reports and statistics, etc.

All organisations are demanding better justification for investments in any KM initiative and expected outcomes. Therefore, we must ensure that KM initiatives are directly linked to the organisation’s business strategy. Moreover, we must also ensure that there are performance measurements in place to evaluate the success of the proposed KMF or KM initiative.

The SMART KMF is unique as it considers a number of paradigms and key organisation facets to assure successful deployment of KM practices and long-term sustainability of the associated benefits.

The purpose of this study is to examine the development of environmental performance (EP) through sustainable practices (SPs), environmental corporate social responsibility (environmental CSR) and behavioural intentions (BIs) among Pakistan’s small and medium enterprises (SMEs).

In this study, the researchers applied a quantitative approach which involved significant cross-sectional data. The authors used an online survey to serve the aim of this study. The survey’s respondents are top managers of Pakistan’s manufacturing firms. The authors received 196 valid cases to obtain suitable outcomes from the data.

By using the structural equation model, the path analysis shows that green practices (GPs) have a positive and significant effect on SPs and environmental CSR. This study’s findings also demonstrate that environmental CSR plays a substantial role in developing the SPs, BIs and EP. The results of this study also show that SP plays a positive and significant role towards BIs and EP. Finally, BI predicts the EP.

This study's findings provide planners and policymakers with guidelines to create EP through environmental CSR, SPs and BIs. This study's findings are valuable results in identifying green practices’ significant role in establishing environmental CSR and SPs. Finally, this study's findings offer a new perception of integrating these factors and their contribution to EP.

This study examined the development of EP in the challenging situation of the COVID-19 pandemic. Therefore, in terms of the empirical findings, this study provides original value.

Nurse turnover in critical care units (CCU) significantly affects patient outcomes and health systems worldwide. To safeguard patient care quality, hospitals must address the underlying reasons for turnover and strategize to retain their skilled nursing workforce. The study proposes a prescriptive framework to reduce nurse turnover in CCUs.

In this study, the integrated methodology of Delphi-AHP-Entropy was used for the comparative prioritization of factors and subfactors that influence nursing staff turnover in CCUs.

Study findings reveal that “Organizational factors” and “Individual factors” dictate critical care nurse attrition rate. At the subfactor level, staffing policy, chronic fatigue, and perceived career are the leading concerns for the decision of nurses whether to work or leave.

This study is valuable for both researchers and healthcare professionals. It examines whether actions related to nurse retention align with existing theory and identifies areas requiring further theoretical or applied studies to enhance understanding in this area. This insight can bolster the field’s knowledge base and integrate theoretical and applied knowledge effectively. Additionally, for healthcare professionals, the study provides an overview of key factors conducive to retaining nursing staff in the CCU, offering valuable guidance for implementing effective strategies.

This study uniquely positions itself by presenting a comprehensive and prescriptive framework for critical care nurse retention in the UAE.

Allocating risk in public–private partnership (PPP) projects based on public–private parties’ risk management (RM) capabilities is a condition for success of these projects. In practice, however, risks are allocated to these parties beyond their respective RM capabilities. Too much risk is often assigned to the private or public party, resulting in poor RM and costly contract renegotiations and terminations. This chapter proposes a methodology based on fuzzy set theory (FST) in which decision makers (DMs) use linguistic variables to assess and calculate RM capability values of public–private parties for risk events and to arrive at risk allocation (RA) decisions. The proposed methodology is based on integrating RA decision criteria, the Delphi method and the fuzzy synthetic evaluation (FSE) technique. The application of FSE allows for the introduction of linguistic variables that express DMs’ evaluations of RM capabilities. This provides a means to deal with the problems of qualitative, multi-criteria analysis, subjectivity and uncertainty that characterise decision-making in the construction domain. The methodology is outlined and demonstrated based on empirical data collected through a three-round Delphi survey. The public–private parties’ RM capability values for land acquisition risk are calculated using the proposed methodology. The methodology is helpful for performing fuzzy-based analysis in PPP projects, even in the event of limited or no data. This chapter makes the contribution of presenting a RA decision-making methodology that is easy to understand and use in PPP contracting and that enables DMs to track calculations of RM capability values.

Tender price remains an imperative parameter for clients in deciding whether to invest in a construction project, and it serves as a basis for tender price index (TPI) manipulations. This paper aims to examine the factors affecting tender price in the construction industry.

Based on the literature review, nine independent constructs and one dependent construct relating to tender pricing were identified. A structured questionnaire survey was conducted among quantity surveyors in Ghana. Partial least squares structural equation modelling (PLS-SEM) examined the influences of various constructs on tender price development (TPD) and the relationships among TPD and TPI.

Results showed that cultural attributes, client attributes, contractor attributes; contract procedures and procurement methods; consultant and design team; external factors and market conditions; project attributes; sustainable and technological attributes; and TPI have a positive influence on tender price, whereas fraudulent attributes exert a negative influence.

The findings offer construction professionals broader understanding of factors that affect tender pricing. The results may be used in professional decision-making in the pricing of construction projects, as they offer clearer causal relations between how each construct will influence pricing.

This study adds to the body of construction pricing knowledge by establishing the relationships and degree of influences of various factors on tender price. These findings provide a valuable reference for practitioners.

This paper aims to study the gravity effects on a micro-elongated thermoelastic layer under a fluid load, utilizing the Lord–Shulman (L-S) theory and the dual-phase-lag (DPL) model.

The analytical method used was the normal mode which partial differential equations transform into ordinary differential equations.

Aluminum epoxy numerical computations are carried out, and the results are graphed. The DPL model and the L-S theory are compared in the complete absence and presence of gravity. Comparisons were also made for three values of and it is observed that the gravity has quite a massive influence on all physical quantities.

In the present paper, the authors shall create the general equation for the energy equation, which includes the two theories (DPL and L-S) as well as the solution of micro-elongated thermoelasticity under fluid load. The problem is pretty important in many dynamical systems.

The purpose of this paper is to propose a research model to identify the key determinants and examine their impact towards online pro-brand and anti-brand community citizenship behaviours (CCBs).

A survey based on the research model is used to collect empirical data from 260 and 200 members of online pro-brand communities (OBCs) and online anti-brand communities (OABCs), respectively. A two-stage approach employing fuzzy-set qualitative comparative analysis and artificial neural network (ANN) is first applied to uncover new observations.

Moral identity and positive brand emotion (BE) are the two most influential factors driving both online pro-brand and anti-brand CCBs. A higher level of internalisation might be required to exhibit online anti-brand CCB as opposed to online pro-brand CCB. This contradicts the current understanding that anti-brand behaviours are less morally restricted given the virtuality and anonymity of online communities. OABC members may need to better justify themselves internally to overcome positive BE when exercising anti-brand action. Also, brand identification, brand dis-identification and BE would be used to identify two types of OABC members.

The effect of motives other than pro-social remains unclear on online pro-brand and anti-brand CCBs.

This is the first paper to develop two new dimensions which provide a more complete definition of CCB. Also, some new observations are uncovered by comparing the effect of different key determinants on online pro-brand CCB against that of online anti-brand CCB. The research model can be used to define and improve member (or brand) engagement which would enhance the management of OBCs and OABCs.

Determining the duration for road construction projects represents a problem for construction professionals in Ghana. The purpose of this paper is to develop an artificial neural network (ANN) model for determining the duration for rural bituminous surfaced road projects.

Data for 22 completed bituminous surfaced road projects from the Department of Feeder Roads (rural road agency) were collected and analyzed using the principal component analysis (PCA) and ANN techniques. The data collected were final payment certificates which contained payment bill of quantities (BOQ) of work items executed for the selected completed road projects. The executed quantities in the BOQ were the total quantities of work items for site clearance, earthworks, in-situ concrete, reinforcement, formwork, gravel sub-base/base, bitumen, road line markings and furniture, length of road and actual durations for each of the completed projects. The PCA was first employed to reduce the data in order to identify a smaller number of variables (or significant quantities) that constitute 81.58 percent of the total variance of the collected data. The ANN was then used to develop the network using the identified significant quantities as input variables and the actual durations as output variables.

The coefficient of correlation (R) and determination (R²) as well as the mean absolute percentage error (MAPE) obtained show that construction professionals can use the developed ANN model for determining duration. The study shows that the best neural network is the multi-layer perceptron with a structure 3-38-1 based on a back propagation feed forward algorithm. The developed network produces good results with an MAPE of 17.56 percent or an average accuracy of 82.44 percent.

Apart from the fact that the sample size was small, the developed model does not incorporate the implications of other likely factors that may affect contract duration.

The outcome of this study is to help construction professionals to fix realistic contract duration for road construction projects before signing a contract. Such realistic contract duration would help reduce time overruns as well as the payment of liquidated and ascertained damages by contractors for late completion.

This paper proposes an alternative way of determining the duration for road construction projects using the total quantities of work items in a final payment BOQ. The approach is based on the PCA and ANN model of quantities of work items of completed road projects.

This paper aims to identify the main non-cost factors affecting accurate estimation of life cycle cost (LCC) in building projects.

Ten factors affecting LCC in building project cost estimates are identified through literature and interviews. A questionnaire survey is conducted to rank these factors in order of priority and provide the views of cost practitioners about the significance of these factors in the accurate estimation of LCC. The data from 138 construction building projects completed in UK were collected and analysed via multiple regression to discover the relationship between capital and LCCs and between non-cost factors and cost estimation at each stage of the life cycle (capital, operation, maintenance and LCC).

The results of analysis of existing LCC data of completing project and survey data from cost professionals are mostly consistent with many literature views and provide a reasonable description of the non-cost factors affecting the accuracy of estimates.

The value of this study is in the method used, which involves analysis of existing life data and survey data from cost professionals. The results provide a plausible description of the non-cost factors affecting the accuracy of estimates.

Knowledge is a fundamental source for sustainability and transfer as it plays a vital role in gaining and maintaining competitive advantage; thus it is imperative to investigate the factors that might impact knowledge transfer (KT). Therefore, the purpose of this paper is to investigate the association between knowledge enablers (organizational culture (OC), information technology (IT) knowledge leadership (KL) and knowledge strategy (KS)) and KT in the Jordanian construction industry.

A quantitative research approach was adopted, and structured questionnaire was sent to the employees in the construction industry. An aggregate of 250 surveys were distributed and out of them 195 were obtained, which represented a response rate of 78 percent.

The results of this paper showed that KS, OC, IT and KL has positive and significant impact on KT.

The study contributes to the literature by empirically testing the antecedents of KT in the Jordanian construction industry. To the best of authors’ knowledge, there are not many studies that incorporate these factors in single model, especially in Jordan.