The impact of technological alignment and advancement on firms’ project performance with mediating role of technology acceptance model 1

Abstract

BACKGROUND:

Nowadays, technology has become a vital capability for the organizations. It plays an essential role for all business operations and performances consequently it is crucial to uncover technological influence with respect to project performance.

OBJECTIVES:

This study examines the linkage of technological alignment (TAL) and technological advancement (TAD) on organizational project performance (OPP) with mediating influence of Technology Acceptance Model (TAM) considering two TAM attributes—perceived ease of use (PEOU) and perceived usefulness (PU) —.

METHODS:

Data were collected using a convenience sampling approach from the respondents associated with different business projects in China and analyzed using structural equation modeling and factor analysis.

RESULTS:

The findings affirmed the positive relationships of TAL and TAD on OPP. The study revealed the mediating influence of PEOU between TAL and OPP. The study further affirmed a positive mediation of PU between TAD and OPP, respectively.

CONCLUSION:

This study provides insights into how incorporation of technological and TAM tools—TAL, TAD, PEOU, and PU—may improve OPP of the organizations in today’s digital era. In addition, the study provides implications for the management and future opportunities for the researchers.

Keywords

Information technology project performance technology acceptance model structure equation modeling

Kamelia Shahid is a PhD research fellow at School of Economics and Management, University of Science and Technology Beijing, China. She is doing research on Global Team Management, IT management, Project management, and International business operations. Her papers appear in international conferences and journals. Kamelia Shahid did Master of Business Administration (MBA) from Wuhan University of Technology, Wuhan, China. She has ten years of working experience in Multinational Company in Beijing, China. E-mail: camelia_013@hotmail.com.

Prof. Dr. Qing Yang is a PhD supervisor and tutor in the school of Economics and Management, University of Science and Technology Beijing. He is supervising national and international students since a long time. The core area of Prof. Qing Yang includes Research involves managing the development process of a complex engineering project, the design structure matrix, design process modeling, optimization and simulation, and lean management in development projects. E-mail: yangqing@manage.ustb.edu.cn.

Dr. Abdul Waheed is Assistant Professor at University of Management and Technology, Lahore. He did PhD marketing from AACSB and AMB accredited business school, University of Science and Technology Beijing, China. He has over 55 publications in SSCI, Scopus, EI, ABS, and ABDC indexed journals, conferences, and books. His teaching and research interests include strategic marketing, digital marketing, consumer behavior, and SCM. E-mail: abdulwaheed168@yahoo.com.

Dr. Yasir Rashid is a graduate of AACSB, EQUIS and AMBA accredited foreign business schools. He is currently serving as the Digital Marketing Consultant of Pakistan under the Ministry of IT and Telecom, Government of Pakistan. He came back to Pakistan from overseas in 2014 after working for multi-billion dollar firms at various roles. He is currently devoting his academic research energies on developing Digital Marketing, Service-Dominant Logic of Marketing, and Value Co-Creation concepts. E-mail: yasir.rashid@umt.edu.pk.

1 Introduction

Technology has become an essential part of all business operations which supports enhancing a firm’s performance in today’s modern era [1, 2]. The living standards of humans also have been transformed toward flouring means of information communication technologies to interact with each other [2, 3]. Therefore, researchers have explored the influence of technology on human activity to study the impact on distinct projects and business operations. The experts have attempted to identify the significance of technology in order to reduce communication barriers and develop easier ways for humans to interact with each other [4]. According to Powell and Dent-Micallef [5], the adoption of technology may be the impetus for humans to work more efficiently and dynamically. The usage of technology is imperative in optimizing the performances in distinct fields such as banking, socialization, procurement, agriculture, and rest of the operational activities of the business [2 , 7]. The experts have been conducted a deep analysis to understand the significance of IT capability in terms of organizational agility and performances across the world [8 –10]. The role of information technology and its adoption is an important factor to determine the success and performance of the organizations [11 –14].

According to Memon, An [1], incorporation of information technology improves the performance of the organizations. Technology is a prime source for business processes in order to survive in today’s digital and dynamic world [9]. Understanding the impact of technology integration on remainder performance including organizational project performance (OPP) got far less attention from experts [9, 14]. There is no known study that examined the role of technological integration concerning to OPP which is the present study gap. Project performance is defined as the management or an ongoing review of the efficiency and importance of a given project [15, 16]. The present study considered technologies in term of IT alignment (TAL) and IT advancement (TAD) to measure the impact on project performances along with the role of the technology acceptance model (TAM) as a mediator. TAL supports the alignment of information technology with insider personnel, and endeavors to align the entire related operation. However, TAD supports the organization’s ability to adopt most advanced tools, state of the art IT, and always prefers to accept latest technologies for better business performance.

In the past, researchers have worked to unveil the influence of technological tools, especially concerning ICTs and IS, across the nations within various domains and to suggest positive outcomes by acceptance and utilization. Such studies revealed the influence of IT with respect to financial performance [17], organizational performance [11 , 14], economic performance [12], and operation performance [18]. However, there is no known study that examined the role of IT considering TAL and TAD factor with respect to organizational project performance (OPP) along with the effect of TAM as a mediator between the linkages of IT integration (TAL and TAD) and OPP. It was important to explore the relationships of technology in order to furnish further evidence and to contribute insightful information to the literature on IT and OPP. By doing so, this study strived to meet the following research objectives.

First, this study aims to examine the relationship between technological alignment (TAL) and organizational project performances (OPP). Second, this study attempts to examine the relationship between technological advancement (TAD) and OPP. Third, this study strives to explore the mediating role of PEOU between TAL and OPP. Finally, this study aims to explore the mediating role of PU between TAD and OPP. To this end, the article is organized as follows. The theoretical support along with hypothesized relationships is presented in this next section. Subsequently, research methodology is reported, including sampling, data gathering procedure, adopted scales, employed tools for data analysis, and the remaining techniques used to complete the study. The discussion, decision regarding proposed hypothesized relations, and findings are also addressed. The final part of the article is comprised of theoretical and management implications for future academic, limitations of the study, and practitioner consideration to replicate our findings.

2 Literature review

The experts have defined project performance as the management or an ongoing review of the efficiency and importance of a given project within a particular time span [16]. In such scenarios, technological integration may perform a crucial role. IS and ICTs tools will be useful in developing voice transmission, texting, and video communications, especially for two streams (individual and group meetings or communications during a particular project) [2, 19]. In such a domain, information technology with respect to ICTs contributes a prime role in optimizing performance concerning project performance. Over the past few decades, various ICTs tools have been utilized for human life in various fields including medical, transportation, business operations, agriculture, consumer study, banking, product design, and industrial contexts [2 , 20–22]. Experts have suggested IT communication is significant and their findings are validated across the economies through the usage of such technological platforms. Such consideration is useful in improving project performance in the digital age. In addition, the relationships between various tools of information technology and organizational performance have been unveiled and validated from the global perspectives [11–14 , 24].

There are diverse models and theories that encourage researchers to analyze the influence of IT acceptance worldwide. Such theories and models include innovation diffusion theory [25]; the technology acceptance model (TAM) was introduced and tested [26]; and, the Unified Theory of Acceptance and Use of Technology (UTAUT) where UTATU2 was introduced and validated in distinct contexts and dimensions across the globe by diverse researchers [27 –29]. Presently, TAM is focused on understanding the mediating role it has between technology and project performance. Two aspects of TAM were used in the present study, i.e., ease of use and usefulness owing to widespread implications of models used in past studies [26].

Several platforms are available that might be used in virtual communications, including Open Course Ware (OCW), Google, team viewers, Facebook, emails, Skype, SMS, Twitter and multiple personal device applications to enable firms to share product information or ideas by creating in a virtual learning environment [30 –32]. The present study focused on IT tools (such as TAL and TAD) to ensure the significance concerning project performance with the mediating effect of technology acceptance model. This study observed that TAL helps to align the partner, internal personnel, and other related operations [33]. In contrast, TAD helps the firms to adopt more advanced tools, develop state of art information technology, and consider advances in ICTs for better business performance [33]. The objectives of the present study was to unveil the relationships of technological dimensions—TAL and TAD— on project performance along with mediation influence of TAM model considering two factors —PU and PEOU— to understand the insights by developing following hypotheses.

2.1 Hypotheses development

2.1.1 Technological alignment (TAL) and organizational project performance (OPP)

Technological alignment (TAL) is an organizational capability being used to better fit all those technologies and certain standards to bring out effective roadmap for organizational success [11]. In the past, research considered TAL in different aspects and dimensions other than organizational project performance (OPP). For an instant, known research considered TAL with respect to infrastructure [34], in terms of strategic alignment [35], as well as social technological alignment [36]. However, there is still a lack of studies that considered TAL in terms of OPP in the existing literature. TAL is an important capability for a business project that can enhance the performance of a particular project [37]. The organizations are more successful that possess the integration of technological tools because business and technology are both necessary for each other in today’s era [37]. Undeniably, scholars have spent much time examining IT, IS, and ICT tools to explore outcomes using distinct domains and dimensions worldwide [11 , 28]. Most of the prior research in the field examined the role such tools influence a firm’s financial performance [13, 24], operational performance [18], banking performance [7], and other related areas of performance [13 , 33]. Such research has affirmed the positive influence of IT on distinct forms of performance. However, no known study has explored the influence of such technologies on project performance. To fill the understanding gap, based on theoretical support and hypothesized relationships, this study attempted to investigate the connection between information technologies on project performance in order to furnish additional evidence of the nexus between the various parts for future scholarly inquiry.

H₁: TAL is positively correlated to OPP

2.1.2 Technological advancement (TAD) and OPP

Technological advancement (TAD) is an organizational capability to develop and integrate more innovative technologies to boost business operations in a more productive manner [38]. Integrating new technologies improve the operational process keeping efficiency and innovation [39]. Over the last decades, firms increasingly relying on technological advancement which ultimately helps to improve the organizational performance [39, 40]. Technology advancement is an important incident of the different performance of the organizations [40, 41]. Over the past decades, several researchers explored the impact of technology integration and revealed the positive connection on organizational performance [1 , 41]. The study of [41] concluded the positive relationships between technology and organizational performance. A study of [42] unveiled the significant relationships between technology and project performance in terms of R&D. In general, there are several studies that have recommended the positive connection between the integration of technology and organizational performance as well as encourages the organizational to advance its technological capabilities [1 , 41]. However, the literature is witnessed that there is still lack of known studies that examined the connection of technological advancement (TAD) on organizational project performance (OPP). This study specifically attempts to uncover the relationships between TAD and OPP with the help of empirical evidence and to contribute in the related literature. To that end and to ensure such relationships, the study currently proposes the following hypothesis.

H₂: TAD is positively correlated to OPP

2.1.3 Technology acceptance model (TAM) as mediator

TAM is a theory of information system (IS) that encourages researchers to accept and explore IT from different perspectives. There are diverse factors that influence decision making on how to use TAM; however, two core factors of TAM were highly used to examine the influence of its acceptability across distinct global domains and dimensions. Such factors of TAM have perceived usefulness (PU) and perceived ease of use (PEOU) [26]. The PU dimension of TAM explains the degree in which an individual believes that particular IS factors may enhance business performance, while PEOU dimensions of TAM explain the degree in which an individual believes that a particular information system (IS) is easy to use [26]. TAM has been globally studied by academicians, policy-makers, and practitioners, whose studies revealed the positive nexus of TAM with dissimilar perspectives and organizational performances [26 , 44]. As research developed in the field, the TAM model was extended from TAM to TAM1 and TAM2 respectively as proposed by Venkatesh and Davis [45] and later tested in various contexts. In the past, TAM model was extensively used in different studies where some researchers have fully utilized TAM dimensions as well as some researchers have used a few dimensions of TAM in order to examine the influence in different contexts globally [46 –48].

However, a few studies used TAM as a mediator other than organizational project performance and by considering TAL and TAD variables over the past decade [49]. In this study, TAM was used as a mediator to observe how its use may enhance the correlation between technological tools (TAL and TAD) and project performance (OPP). In the past, there no known study that considered TAM as a mediator between TAL and OPP. It is noteworthy to mention a few factors of TAM have been used as a mediator in a limited number of past studies [49, 50]. However, no known study examined the influence of TAM factors between IT acceptance and project performance. Based on the above significance and theoretical support, the following hypotheses are developed in order to explore the relationships as follows.

H₃: PEOU mediates the correlations between TAL and OPP

H⁴: PU mediates the correlations between TAD and OPP

3 Methodology

3.1 Data collection procedure

Data were collected between December 2018 and April 2019 using a convenience sampling approach from respondents attached to distinct projects in China. Convenience sampling is used because of its more convenient and ease to collect data from respondents. Inspired byKing, Cassell [51], quantitative tools were used that support the researchers with a clear and reliable investigation. A total of 300 questionnaires were carefully circulated using online techniques such as Google Doc and emails. Of the total, 250 samples were finally considered for data analysis after the elimination of inappropriately filed documents. The questionnaire document s consisted of two sections: the demographic record of the respondents (see Table 1) and core questions related to the main study (see Table 6).

A five-point Likert scale was used, which was ranged from strongly disagree to strongly agree, following previous study benchmarks [e.g., 28, 52]. 1 was coded for strongly disagree, 2 for disagree, 3 for neutral, 4 for agree, and 5 for strongly agree. Similarly, 1–5 numbers were dedicated to record demographic profiles of the target respondents. The survey documents covered 21 statements for adopted variables along with demographic questions. Information technology was adopted as the independent variable, project performance (OPP) the dependent variables, and technology acceptance model (TAM) as a mediating variable considering two factors: perceived ease of use (PEOU) and perceived usefulness (PU).

All statements were culturally personalized and piloted for better research results. A pre-study test was conducted to observe the feasibility, reliability, and validity of the variables since Van Teijlingen, Rennie [53] encouraged researchers to affirm the preliminary creditability of the constructs before larger data collection. A total of 30 surveys were initially piloted and examined by means of Cronbach alpha values as suggested by DeVellis [54]where the outcome values must >0.7. The results unveiled the accuracy of the adopted constructs showing values for OPP and TAM higher than >0.7 where TAL stands at α= 0.78, TAD at α= 0.80, OPP α= 0.80, PEOU at α= 0.74, and PU at α= 0.75, respectively.

3.2 Measures of constructs

Three kinds of the variables were adopted for measurement: TAL and TAD as the independent variable, OPP as the dependent one, and TAM as the mediating variable. All scales were adapted from previous studies where TAL and TAD adopted from Wu, Yeniyurt [33]. Second, OPP was measured by three scales adopted from Daim, Ha [55]. Third, TAM was measured by two factors, PEOU and PU, as adopted from Davis [26]. All the latent variables items are reported in Table 6 along with the validity and reliability of each construct/item.

3.3 Data analysis

SPSS and SmartPLS software were employed for data analysis and hypotheses examination where PLS/SEM approach was used as inspired from the past related studies [2 , 56]. Using such tools, five core statistical techniques were utilized to obtain the results: descriptive statistics (see Table 1), confirmatory factor analysis (CFA) (see Table 6), Pearson’s r correlation (see Table 5), discriminate validity (see Table 4), and structure equation modeling (see Table 7). First, information related to demographic profiles was generated using descriptive techniques considering five respondents’ attributes: gender, age, education, experience, and salary packages as reported in Table 1. Second, CFA was employed to affirm validity using loadings and AVEs, with reliability using composite reliability.

The outcome values for loadings and AVEs should be higher than 0.05, while composite reliability should be higher than 0.7 [57 –59]. Third, correlation among latent variables, (IV, DV, and MV) were evaluated using Pearson’s r correlation technique, which Taylor [60] suggested higher positive values show higher connection, while lower or negative values indicate weak or negative relationships. Fourth, discriminate validity was calculated to confirm the degree of differentiation among latent constructs and items (see Table 4). Deng, Mo [61]) suggested that √AVEs could be compared with the inter-correlation of subsequent items where the values of √AVEs must be higher than subsequent item’s interrelationships.

Finally, SEM was implemented to affirm the major path relationship between IT and OPP along with the connection of TAM as a mediator between IT and OPP at a significant level 0.05 (see Table 7). A standardized root mean squared residual (SRMR) was considered to meet model fit criteria of the structure equation model (SEM) since Hu and Bentler [62] recommended the value of SRMR should be lower than 0.08 for accuracy in structural model. In the current study, the value of SRMR stands at 0.0710 which ensures a model fit [62]. Furthermore, a random sub-sample of 4000 was used to understand the insight accuracy of the collected data while using SmartPls for bootstrapping (see Table 7). The SmartPls tool has the capability that allows the users to select inside additional sub-sample other than the main sample to ensure the stability of the collected data [63, 64].

4 Results and findings

Table 1 shows the demographic attributes of target respondents. In this study, four dimensions of the respondents were examined such as gender, age, education, and experience. First, the study demographics show there were there higher numbers of male respondents in this study (60%) as compared to females (40%). Second, 6.0% respondents were 18–23-year-old, 12% were 24–29-year-old, 72% were30–35-year-old, and 10% were respondents over 36-years-old. Third, 8% of respondents hold a bachelor’s degree, 24% has a master’s degree, 60% have MS/Mphil degrees, and 8% obtained a PhD, other professional diplomas, or certificates. The fourth attribute category for the subjects was as follows. 10% respondents have 2–5 year of working experience, 16% respondents have 6–9 year of working experience, 60% respondents have 10–13 year of working experience, and 14% respondents have >14 year of working experience.

Table 1
Demographic Findings

Attributes Frequencies %

Gender (male = 60%; female = 40%)

Qualification level

Bachelor’s degree 20.0 08.0

Master’s degree 60.0 24.0

MS/Mphil degree 150 60.0

Others^* 20.0 08.0

Age level

18–23 year 15.0 06.0

24–29 year 30.0 12.0

30–35 year 180 72.0

>36 year 25.0 10.0

Working Experience

2–5 years 25.0 10.0

6–9 years 40.0 16.0

10–13 years 150 60.0

>14 years 35.0 14.0

Attributes	Frequencies	%
Gender (male = 60%; female = 40%)
Qualification level
Bachelor’s degree	20.0	08.0
Master’s degree	60.0	24.0
MS/Mphil degree	150	60.0
Others^*	20.0	08.0
Age level
18–23 year	15.0	06.0
24–29 year	30.0	12.0
30–35 year	180	72.0
>36 year	25.0	10.0
Working Experience
2–5 years	25.0	10.0
6–9 years	40.0	16.0
10–13 years	150	60.0
>14 years	35.0	14.0

n = 250; ^*PhD degree or remainder professional courses and diplomas holders.

Table 2 shows the overall metrics and constructs in order to measure the specific latent variables such as independent and dependent variables. Five latent variables were used in which two were independent variables; two were mediating variables, while one was a dependent variable. The detailed description of each variable is shown below in Table 2.

Table 2

Description of the Constructs

Construct	Measurement model	Number of indicators	Pre-reliability
TAL	factor (Mode A)	5	1.000
TAD	factor (Mode A)	5	1.000
OPP	factor (Mode A)	3	1.000
PEOU^*	factor (Mode A)	5	1.000
PU^*	factor (Mode A)	3	1.000

Note: OPP = project performance; PEOU = perceived ease of use; PU = perceived usefulness; ^*TAM factors; TAL = technological alignment; TAD = technological development.

Table 3 represents the values for means, alpha, SD, and AVEs. All values are normal with alpha values higher than the level of 0.7 and AVEs are higher than the level of 0.5, which indicates the accuracy of the values. The values of means and SD are presented below in Table 3. According to experts, the values of AVEs and alpha should be higher than.7 for alpha and higher than 0.5 for AVEs [57, 58].

Table 3

Overall Description of the Constructs

	Latent variables	Mean	SD	α	AVEs
1	TAL	3.350	0.851	0.752	0.721
2	TAD	3.824	0.832	0.735	0.801
3	OPP	3.234	0.750	0.801	0.745
4	PEOU	3.125	0.831	0.798	0.763
5	PU	3.335	0.818	0.748	0.815

Note: OPP = project performance; PEOU = perceived ease of use; PU = perceived usefulness; ^*TAM factors; TAL = technological alignment; TAD = technological development.

Table 4 indicates the values of discriminate validity. Discriminate validity is defined as the extent to which constructs of the study are conceptually evaluated either as adopted variables that are correlated or not correlated to each other [61]. According to experts, the square root of AVEs values should be compared with the relationships of corresponding values of the adopted variables [57 –59]. Furthermore, such researchers recommended the values of square roots of AVEs should be higher than the values of corresponding interrelationships of the variables in order to ensure the validity of discriminate among the variable [57, 65]. The results of the discriminate validity are presented in Table 4.

Table 4

Discriminate validity

	TAL	TAD	OPP	PEOU	PU
TAL	0.849
TAD	0.342	0.894
OPP	0.255	0.254	0.863
PEOU	0.490	0.354	0.254	0.873
PU	0.634	0.540	0364	0.251	0.890

Squared correlations; AVE in the diagonal.

Table 5 indicates the values of correlations where Pearson’s r is employed to calculate the association among the adopted variables. The values show the interrelationships between the variables and the positive linkage between variables. Experts recommended that the higher values indicate the strong positive connection while the week values indicate the weaker connections between such particular variables [48]. In this study, the researchers used two kinds of constructs such as independent and dependent variables and the values showing such interrelationships (see Table 5).

Table 5

Correlation Matrix of the constructs

	TAL	TAD	OPP	PEOU	PU
TAL	1.000
TAD	0.235	1.000
OPP	0.285	0.354	1.000
PEOU	0.325	0.248	0.351	1.000
PU	0.354	0.463	0.214	0.432	1.000

Higher values show higher correlation, while lower values indicate lower correlation.

Table 6 indicates the values of confirmatory factor analysis in which different values are calculated in order to affirm the reliability and validity of the adopted constructs. The discriminate validity has already been calculated through confirmatory factor analysis and unveils the values for the overall validity and reliability of the constructs. In this study, the validity of the constructs was examined with the help of average extracted variance and loadings for each item of the constructs. Prior researchers hypothesized the values of composite reliability that must be higher than 0.7 whereas the values of AVE should be higher than 0.5 [57]. The values as presented in Table 6 affirm the validity and reliability of all the adopted variables in this study. The means standard deviation values are reported along with the values of composite reliability and average extracted variance.

Table 6

Confirmatory factor analysis

Latent variables	Items	Mean	SD	LDs	AVEs	CR
TAL					0.721	0.81
Our IT is well aligned with our partner	ITA1	3.25	0.85	0.65
Our business invest in IT to align with our partner	ITA2	3.12	0.86	0.64
Our partner invests in IT to align technology with us	ITA3	3.65	0.84	0.63
We and our partner work together for the best IT align	ITA4	3.58	0.75	0.59
TAD					0.801	0.78
We use the most advanced IT	ITAS1	3.25	0.74	0.69
Our IT for is always state-of-art	ITAS2	3.65	0.73	0.64
Our IT is more advanced than competitors	ITAS3	3.33	0.89	0.63
We use new IT for our industry	ITAS4	3.15	0.84	0.68
We regarded IT as leader in our industry	ITAS5	3.24	0.84	0.65
OPP					0.745	0.77
How would you rate your overall project Performance	OPP1	3.54	0.83	0.66
How you rate your ability to complete assignments	OPP2	3.65	0.84	0.63
How would you rate quality of your performance	OPP3	3.14	0.75	0.58
PEOU					0.763	0.80
Learning to use the website is easy	PEU1	3.45	0.76	0.64
It is easy to get the website to do what I want	PEU2	3.21	0.70	0.61
The interactions with the website are clear	PEU3	3.32	0.87	0.60
The website is flexible to interact with	PEU4	3.62	0.89	0.70
The website is easy to use	PEU5	3.96	0.83	0.58
PU					0.815	0.76
The online system is fast	PU1	3.19	0.78	0.65
It is easy to use online system	PU2	3.12	0.79	0.69
This system is useful for information sharing	PU3	3.24	0.84	0.60

Note: Factors having <0.5 AVEs and loadings were removed; LD = factor loadings; SD = standard deviations; CR = composite reliability.

Table 7

Structure equation modeling and decision on hypotheses

Factors and relationships on OPP	PCA	Sig.	Decision
H1: TAL ⟶OPP	0.465	0.001^*	Supported
H2: TAD ⟶OPP	0.354	0.000^*	Supported
H3: TAL ⟶PEOU⟶ OPP	0.265	0.000^*	Supported
H4: TAD ⟶PU⟶ OPP	0.404	0.000^*	Supported

^*Level of Sig = 0.05; level of SRMR = 0.0710. OPP-organizational project performance; PCA = path coefficients: TAL-technological-alignment; TAD-technological development; PEOU = perceived ease of use; PU = perceived usefulness.

Table 7 and Fig. 1 indicates the decision regarding three hypotheses of this study as examined using SEM, to ensure the relational direction between variables. Since three kinds of variables were used, OPP is taken as DV while two variables such as TAL and TAD were adopted as independent variables. Likewise, TAM was employed as a mediating factor between IT and OPP using the two factors of TAM, i.e., PEOU and PU (see Table 6). The findings show positive connections between the first assumed relationships where SEM results show the positive connection of IT on OPP at (β= 0.465^*; p = 000). Second, SEM results indicate a positive mediation connection of the PEOU factor of TAM at (β= 0.565^*; p = 000).

Fig.1

Structure model.

Third, SEM results reveal a positive connection of the PU factor of TAM at (β= 0.404^*; p = 000). Furthermore, all findings of SEM represent the positive connection of all independent variables on dependent variables along with mediation influence of TAM toward OPP. The remainder detail such as level of significance and adopted model fit index for this study are reported underneath the following Table 7. Scholars recommend criteria be used for model fit indices such as the standardized root mean squared residual (SRMR). According to Hu and Bentler [62], the SRMR value must be less than 0.08 to accept the model fitness. The current SRMR values are 0.0710 which accurate as per recommended criteria [62].

5 Discussion and implications

Nowadays, business operations have shifted toward advanced and evolving means of information technology in order to improve the operational efficiency of the firms. Technology has become the key factor for the success of the organizations therefore organizations are greatly focusing on such capability in order to bring operational efficiency and to boost organizational performance. In the past, diverse experts and academicians have been revealed the positive connection between distinct technological tools and organizational performance. This present work revealed the influence of TAL and TAD on OPP. To that end, four hypotheses were proposed to ensure the significance of TAL, TAD, and TAM on organizational project performance (OPP). The findings reveal positive connections between TAL and OPP relationships where SEM results showed the positive connection between TAL and OPP at (β= 0.465^*; p = 000). Second, SEM results showed a positive connection between TAD and OPP at (β= 0.354^*; p = 000). Third, the results posit a positive connection of PEOU between TAL and OPP at (β= 0.265^*; p = 000). Fourth, the results posit a positive connection of PU between TAD and OPP at (β= 0.404^*; p = 000). Furthermore, all the findings are vividly represented a positive connection of all independent variables and mediating variables on dependent variables. Moreover, for model fitness of SEM, experts recommend the use of criteria for model fit indices such as SRMR, in which experts suggested the higher positive outcome values suggest higher model fit whereas the lower positive outcome value after structure equation modeling indicates the lower model fit index [62]. However, according to Hu and Bentler [62], the SRMR value must be less than 0.08 to accept the model fitness. The current SRMR values are 0.0710 which meets the recommended criteria [50]. Besides, our findings indicate the positive mediation of TAM (PEOU and PU) between the relationships of TAL and OPP. Moreover, partial mediation of PU factor was observed between TAD dimension and OPP, while full mediation of PEOU was found between TAL dimension and OPP, respectively. Hence, the findings concluded the significant impact of technology both TAL and TAD which positively influence the organizational project performance. TAM factors such as perceived ease of use (PEOU) and perceived usefulness (PU) were also found significant mediators between technology and organizational project performance.

5.1 Theoretical implications

This study reports important insights regarding the adoption of information technology and project performance for management. It is essential for firms to adopt emerging and innovative tools information technology such as ICTs to connect with distinct stakeholders of the firms. The study amplifies that acceptance of TAL and TAD in business operations could be productive for firms’ project performance in a dynamic manner. Moreover, from a theoretical, this study offers important theoretical and managerial implications that enlighten the significance of technology and TAM in achieving project performance while empirically contributing to the respective literature of this field. This study contributes to the literature with multidimensional analysis by revealing the nexus of TAL and TAD on OPP with the mediation effect of TAM using two dimensions, i.e. PEOU and PU which affirm a unique contribution in the existing literature.

5.2 Managerial implications

Managers are encouraged to comprehend the essentiality of technological tools, i.e., technological advancement (TAL) and technological development (TAD) which might be helpful in improving the competency of distinct business projects. The management of the organization is encouraged to emphasize such evolving tools, i.e., TAL and TAD to improve the operational efficiency of any business projects and project performance. In this context, there must be ease of use and useful features to conduct meetings as well as communications among related personnel since the current study revealed the positive influence among the ease of use and usefulness dimensions with respect to project performance. The managers are additionally encouraged to understand the insights of technological advancement for business activities along with technological development since the present article has also uncovered the positive connection of such factors toward project performance of the organization. Likewise, managers are suggested to realize the importance of TAM factors in for business context where this study found the positive mediation of both TAM factors toward organizational project performance. The present findings of this study are consistent with previous studies where experts, academicians, and practitioners have been confirmed the importance of technology in distinct business operations and performances [11 , 50]. Finally, this study attempts to provide an overall roadmap to the concerned management on how the incorporation of advanced technology integration might be fruitful for organizational performance, particularly project performance in the current digital era.

6 Conclusion, limitations, and future opportunities

This study highlights the significance of IT concerning to OPP. Although authors believe that diverse factors facilitate organizational communication through the adoption of technological tools such as TAL and TAD to enhance OPP since both factors are found as important determinants of performance. How to manage projects and team is a challenge for the organizations to accomplish the firm’s tasks as a dynamic way creating dynamic collaboration. This study concluded that firms can improve OPP through the incorporation of technological tools. It is further concluded that dimensions of TAM—PEOU and PU— are the important determinants that support the relational strength between technology and OPP. Therefore, the study encourages a firms’ management to pursue such technology and TAM tools in improving OPP in today’s competitive and digital era.

6.1 Limitations and future work

The study has several weaknesses that academic researchers and practitioners should consider in performing their own future studies. First, the study examined the effect of TAL and TAD toward OPP utilizing a sample of 250 subjects due to time and budgetary limitations. This study also considered just two factors of TAM; whereas, other factors might be tested as mediators or moderators between the relationships of IT and OPP. The present study’s sample attempted to furnish empirical evidence from one developing nation (China), it does not represent empirical evidence that could be applied to all countries considered in that category. This study did not explore the moderating influence of any other variables to affirm the intensity of the relationship between IT and OPP.

Future recommendations for academicians and practitioners include as follows. First, a longitudinal design might be considered in the future with a higher sample size within diverse dimensions across the globe. Second, a study could be considered toward remainder larger geographic regions of China to validate the findings in future. Third, a future study might be acknowledged with moderations such as demographic factors, political or environmental factors in order to confirm the connection between information technology and project performance. Fourth, a future study might be expanded to examine the role of information technology toward organizational performance other than OPP. Finally, the researcher might be considered a study with different contexts and dimensions within China and within other economies to validate the findings by providing additional empirical evidence.

Author contributions

CONCEPTION: Kamelia Shahid

METHODOLOGY: Kamelia Shahid and Abdul Waheed

DATA COLLECTION: Kamelia Shahid and Yasir Rashid

INTERPRETATION OR ANALYSIS OF DATA: Kamelia Shahid and Yasir Rashid

PREPARATION OF THE MANUSCRIPT: Kamelia Shahid and Abdul Waheed

REVISION FOR IMPORTANT INTELLECTUAL CONTENT: Kamelia Shahid and Abdul Waheed SUPERVISION: Qing Yang

Footnotes

Acknowledgments

This study was supported by the National Natural Science Foundation of China under funding Number: 71472013, Number: 71872011, and Number: 71528005.

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