The Nexus Between IT Capabilities and Firm Innovation Performance: The Mediating Effect of Supply Chain Agility

Abstract

This study investigates the impact of IT capabilities on firm innovation performance. Further, it examines the mediating role of supply chain agility (SCA) as well as the moderating effect of innovation orientation (IO). The proposed conceptual model draws on resource-based view (RBV) theory. Dataset of 335 responses was analysed with process MACRO using SPSS 24.0 and AMOS. The findings show that IT capabilities positively affect firm innovation performance and SCA mediates the relationship of IT capabilities and firm innovative performance. Finally, results also confirm the moderating effect of IO between the IT capabilities and SCA.

Keywords

IT capabilities innovation orientation supply chain agility firm innovation performance

Introduction

In today’s highly dynamic and uncertain globalised world, firms must innovate by frequently generating new ideas and launching new products and services to keep up with the competition and make more profits (Dilberoglu et al., 2017; Sein, Y. Y., & Vavra, M. 2020). Firms are constantly looking for new ways to innovate and are becoming increasingly aware of adapting to the challenges of the ‘new normal’ through their operations, strategies and routines (Loureiro et al., 2021). Due to digitalisation and globalisation, the domestic as well as the global markets have become highly competitive where the existing products may not help the firm to achieve strategic competitiveness or earn above-average returns. Therefore, market share and sales growth progressively depend on the manufacturer’s skill to stimulate the current market or to enter a new segment of market by introducing innovative products or services (Um, 2017a). Firms employ digital tools to optimise and enhance efficiency of their processes to ensure corporate success. IT capabilities are gaining popularity and are considered as one of the core capabilities for innovation performance due to the highly changing and turbulent environment (Jabbouri et al., 2016; Zhen et al., 2021).

IT capabilities composed of two components (1) flexible IT infrastructure, which is a prudently planned and established technological base on which present and future IT applications are built (Ray, 2005; Scheibehenne et al., 2010) and (2) IT assimilation, or the skill to diffuse and routinise applications of IT in business practises (Armstrong & Sambamurthy, 1999). IT capability has dramatically transformed the traditional ways of doing business by redefining business processes and relationships in different industries, leading to changes in the basis of competition among supply chain firms (Chae et al., 2018).

Supply chain agility acts as an operational capability, which is essential in improving firm innovative performance (Ngai et al., 2011). Supply chain agility is a firm’s ability to execute operational activities together with other channel allies in order to adapt, operate or quickly respond to dynamic business environment (Braunscheidel & Suresh, 2009). Supply chain agility has been known as the most effective strategy for firms willing to gain sustainable competitive advantage through enhanced innovation performance (Liu et al., 2016). Innovation performance of the firms is the degree to which they introduce inventions into the market in terms of new products, new process systems or new devices (Çömlek, 2012). Existing literature highlights the link between IT capabilities and performance of the firm (Liu et al., 2016), while the relationship of IT capabilities with firm innovative performance is unexplored. Moreover, the basic framework through which IT capabilities strengthen innovation performance of firm remains unclear (Yeniyurt et al., 2019). Therefore, scholars have urged to conduct more quantitative studies on the influencing IT capabilities framework, especially in the context of the supply chain (Kim, 2017). Advances in information technology have led many researchers to investigate the role of IT capabilities in enhancing supply chain agility (SCA) (Liu et al., 2016; Mao et al., 2016). This study is an endeavour to fill this gap.

Existing research also lacks studies investigating the effects of information technology on supply chain management practises such as SCA (Mao et al., 2016), in particular, to realise IT capabilities as a competitive tool in establishing agility throughout the supply chains (Peng et al., 2016). In this context, we propose that SCA enhances the effects of IT capabilities on firm innovation performance.

Furthermore, to further elaborate the positive effect of IT capabilities on SCA, this study examines the innovation orientation as a moderating variable between IT capabilities and SCA. Andonova and Losada-Otálora (2020) conceptualised innovation orientation as a source of guidance for strategy formulation and execution that in turn increases the firm’s overall innovativeness. Innovation-oriented firms improve their core competencies in certain resource allocation areas such as technology, supply chain operations, employees and markets (Pantano et al., 2017). Therefore, we propose that when innovation orientation is high, the relationship between IT capabilities and SCA will be more strengthen.

Under the resource-based view (RBV) theory (Barney, 1991, 2001), firms can achieve strategic competitiveness by efficiently utilising both tangible and intangible resources, which need to be reconfigured and coordinated through strategic yet dynamic capabilities (Peteraf et al., 2013). However, so far literature at the intersection of strategic management and digitalisation is unclear to what extent firms’ resources and capabilities (IT) contribute to develop a competitive advantage based on a firm innovation orientation/strategy. The limited theoretical and empirical evidence on the impact of IT capabilities on firm innovation performance is very surprising, as both the academic research and industry reports indicate that firms’ IT capabilities (Davenport et al., 2020), skills (Gartner, 2020), and other intangible and human resources (Verhoef et al., 2019) are critically important for driving digital transformation in business to further enhance firm innovation performance (Rajapathirana & Hui, 2018). Considering this knowledge gap and building on the RBV theory of the firm (Barney, 1991; Peteraf et al., 2013) and on the notion of IT capabilities within digital transformation (Gurbaxani & Dunkle, 2019), the main objective of this study is to examine the effect of firms’ resources, that is, IT capabilities and supply chain agility on their ability enhance innovation performance with an innovation orientation. Therefore, we address the following inter-related research questions:

Do IT capabilities positively influence firm innovative performance?

Does SCA mediate the relationship between IT capabilities and firm innovation performance? and

Does innovation orientation moderate the relationship between IT capabilities and firm innovation performance?

Literature Review and Hypotheses Development

Information Technology Capability and Firm Innovative Performance

Survival in the highly competitive and dynamic 21st century hankered the organisations to develop the technological capabilities for sustainable business outcomes (Turulja & Bajgoric, 2016). IT capability referred to the firm’s ability to operate in digital IT network for the right creation, control and execution of business transactions with right configuration of resources. Oláh et al. (2018) highlighted that IT capability is a tri-dimensional construct that represents a sovereign approach for strategic business restructuring including managerial IT capability, technical IT capability and human support. The adoption and effective use of IT capabilities drive the organisations towards innovation-oriented business performance that requires the right deployment and integration of IT into organisational design, systems, procedures and processes (Chang et al., 2015; Mao et al., 2016). Information technology entitled ‘spindle of organisational competitiveness’ that redirected the organisational focus and investment towards IT enrichment and revolutionary measurements in organisational resourcefulness and dynamism (Kim, 2017). More specifically, Bessen (2017) stated that information technology could even restructure the industrial activities and processes, fields of competitiveness and exploitation of emerging opportunities in the marketplace. Previous researchers claimed that from the last few decades, the business value of IT capability remained the grave concern of practitioners and scholars that ultimately affect the business/firm performance. Performance is a multifaceted construct that can be assessed and measured by the monetary and non-monetary criteria put the firm in the green circle (star performers) of competitiveness (Antoni et al., 2020). The firm innovative performance can be viewed with the lenses of product innovation, process innovation, structural innovation, market innovation that is purely contingent with the technological capability view (Chen & Tsou, 2012; Rajapathirana & Hui, 2018). It is asserted that technological capability is claimed as ‘comprehensive set of characteristics that involves deployment, implementation and integration of numerous organisations activities and process to ensure market competitiveness and ultimate innovative firm performance’ (Lindh & Nordman, 2017). Additionally, existing research has highlighted the direct effect/association of IT capability and firm innovative performance (Chen et al., 2012; Lang et al., 2012; Lindh & Nordman, 2017). Therefore, we can hypothesise that,

H₁: Information technology capability is positively related to firm innovative performance.

Supply Chain Agility as a Mediator

IT capability is considered as a ‘competitive tool’ to sense and scan unexpected market challenges and convert them into efficacious business opportunities (Liu et al., 2013). Nowadays, the contribution of IT capability in agile supply chain environment is highly noticeable for the researchers and practitioners (Dehgani & Navimipour, 2019). Lu and Ramamurthy (2011) claimed that IT is an enabler of supply chain agility that expedite the organisation to reconsider the IT investment and develop superior IT capabilities (at both individual and organisational level) that ultimately lead to successful and innovative business operations. Moreover, Sharma et al. (2017) and Lu and Ramamurthy (2011) conceptualised ‘supply chain agility’ into two dimensions; market capitalising agility, operational adjustment agility and ‘information technology capability’ into IT infrastructure capability, IT business spanning capability and IT proactive stance. IT capability automates various routine jobs and activities such as the operation and distribution practises to create value in overall chain of supply (Li & Chan, 2019). Antoni et al. (2020) highlighted the significant contribution of firm IT capability in information management system, supply chain collaborations, cost reduction, quality enrichment, high profitability and many more. Furthermore, extensive literature accentuated the benefits of information technology for agile organisations that extended from operational gains to the formation of strategic competencies for effective and innovative firm performance (Abdallah & Ayoub, 2020; Al Humdan et al., 2020; Chae et al., 2018; Dubey et al., 2021; Melián-Alzola et al., 2020). Whereas, supply chain agility is a crucial requisite for the innovation-oriented organisations to perform in expeditiously dynamic business world (Um, 2017b). The term ‘agile’ entails the firm’s capacity to spot and consummate the unpredictably and ever- changing demands of customers (Ayoub & Abdallah, 2019; Um, 2017a,b). Therefore, firms are required to come up with flexible and rapid supply chain responsiveness in order to cope with the unexpected and unprecedented challenges of competitive business era (Fayezi et al., 2017; Gligor et al., 2015).

Existing research discussed the concept ‘agility’ as a critical higher-order firm capability to consistently deliver innovative, effective and competitive business performance (Dubey et al., 2018; Eckstein et al., 2015; Gligor et al., 2015). More specifically, agility is the imperative supply chain tool to operate in volatile business environment that has a positive impact on financial, operational and market performance as well (Liu et al., 2016; Tse et al., 2016).

Similarly, few other empirical researches confirmed the direct link of supply chain agility and firm innovative performance (Aslam et al., 2018; Ezgi et al., 2017). Moreover, Eckstein et al. (2015) highlighted the fact about IT-enriched agile firms having better performance than lean firms. Since agile firms are more focused towards rapid and continuous variation in customer’s demands/requirements and ultimate innovation-oriented performance (Tse et al., 2016).

H₂: Supply chain agility mediates the relationship between information technology capability and firm innovative performance.

Innovation Orientation as a Moderator

Andonova and Losada-Otálora (2020) conceptualised innovation orientation as a basic rule for strategic redirection, resource allocation and its implementation that foster the firm overall innovativeness. It is an overarching framework that motivates organisational programmes and systems to manage dynamic environment for effective reflection of firm innovative performance (Pantano et al., 2017). Innovation-oriented firms are open to new ideas, advanced technological tools, networks, capabilities, competencies, skills and structure to ensure supply chain agility that will ultimately lead to competitiveness and innovative performance (Cakir & Adiguzel, 2019; Zaman et al., 2020). It reflects the risk-taking behaviour of an organisation to design and develop new products, processes and systems according to the requirements and expectations of supply chain partners that exhibited firm long-term innovativeness (Rasi et al., 2019; Simpson et al., 2006). According to Norris and Ciesielska (2019), the elements of the innovation orientation knowledge structure comprise a learning ideology, strategic direction and the trans functional philosophies within the organisation that develop innovation-enabling competencies and lead to certain innovation outcomes. Due to this conceptualisation, firms that are innovation-oriented cultivate core organistional competencies in resource allocation, operations, technology, employees, markets and many more (Colclough et al., 2019; Lai et al., 2016; Sundström et al., 2016,).

Based on the empirical findings, we argue that the relationship between IT capabilities and supply chain agility would be more strengthened in the presence of innovation orientation. It is because a high degree of innovative orientation increases the ability of the firm to identify and exploit opportunities via its conducts and actions (Dobni & Klassen, 2015; Yu & Lee, 2017). Consequently, innovation-orientated firms would fully utilise the available IT resources to create a highly responsive supply chain network for superior and innovative firm performance (Pantano et al., 2017; Zaman et al., 2020). Following the aforesaid logical arguments, we believe that innovation-oriented firms are capable enough to translate heightened levels of available information technology capabilities into greater supply chain agility to effectively survive in unprecedented threats of the business environment. Hence, as a moderator within the proposed relationship between information technology capabilities and supply chain agility, we posit as follows:

H₃: Innovation orientation moderate the relationship between information technology capability and supply chain agility (Figure 1).

Figure 1.

Notes:

Data and Method

Participants and Procedures

To investigate the relationship between the proposed variables in the research framework, we collected data from 335 respondents from 14 firms in manufacturing and services sectors of Pakistan (including educational institutions, telecommunication, electronics and garments companies) through a structured questionnaire adapted from prior research. This method was used to enhance the generalisability of the results because of the data taken from the different functional groups (Dooley, 2001).

The convenience sampling method was used to collect the data. Three of the authors have personal relations with the human resource (HR) departments of these organisations. The authors have briefed the HR officers first regarding the study objectives and then they get the official approval for data collection from the higher authorities of the respective organisations. After that an online version of the questionnaire with a cover letter was sent to the employees through the internal mailing system of their organisations. The cover letter explained the research purpose and ensured that the responses will be kept confidential, and data will be used only for research purposes. Also, explained that your participation is voluntary and can withdraw at any stage of filling out the questionnaire. The data were collected for about three months from Feb 2021 to April 2021.

A total of 587 questionnaires were sent, out of which 349 employees responded. After excluding the incomplete questionnaires, 335 were left to test the proposed model. The response rate was 57%. The demographic details of the respondent are given in Table 1.

Table 1.

Sample Demographics.

Variables	Categories	Number	Percentage	Skewness	Kurtosis
Industry	Manufacturing	146	43.6	−0.260	−1.964
	Services	189	56.4
	<100	77	23.0
Employees in organisation	100–1,000	93	27.8	−0.007	−1.407
	1,000–2,000	68	20.2
	>2,000	97	29.0
	<5	102	30.4
	5–10	65	19.4
Employees in IT Department	10–15	30	9.0	0.152	−1.582
Employees in IT Department	15–20	55	16.4
	>20	83	24.8
Organisations	Education	75	22.4	−0.122	−1.344
	Telecommunication	92	27.5
	Electronics	38	17.9
	Garments	108	32.2
IT Capabilities				−0.671	−0.909
Innovation Orientation				−0.586	−0.957
Supply Chain Agility				−0.979	0.145
Firm Innovative Performance				0.238	−1.192

Measure

We adopted measures from prior research and modified them according to our research context.

IT Capabilities: In the current study, IT capabilities play the role of independent variable. We adopted 11 items for IT capabilities from the studies by Bharadwaj et al. (1999), Chen and Tsou (2012) and Turulja and Bajgorić (2016).

Innovation Orientation: Innovation orientation in this study is used as a moderating variable. We adapted innovation orientation from the study by Chittoor et al. (2015) and measured with 6-item scale.

Supply Chain Agility: Supply chain agility is playing a mediator role in the proposed model. It was measured with 12-item scale and adapted from the study by Aslam et al. (2018), Ayoub and Abdallah (2019), Dubey et al. (2018), Şahin et al. (2017) and Um (2017).

Firm Innovative Performance: Firm innovative performance was measured with 4-item scale, and adapted from the study by Gloet and Terziovski (2004).

Data Analysis

We employed Process MACRO using SPSS 24.0 to validate and confirm the proposed hypotheses of the study. Before the main data analysis, dataset was filtered to mitigate the issues of outliers, wrong coding, multicollinearity and missing values (Hair Jr et al., 2017). The findings reflected no errors in the dataset, and thus can be used for further data analysis.

Results

Measurement Tests

Podsakoff et al.’s (1990) recommendations were followed to check out the common method bias (CMB) issue. First, Harman’s single-factor technique was used and the result shows that the first factor explained 36.35% of the total variance, which was lesser than the criterion value of 50% (Harman, 1976), indicating that CMB is not an issue in the data. Second, by comparing the inter-correlation values of all the variables depicting none of the value greater than 0.90, which shows that the data is free from CMB.

The composite reliability (CR), average variance extracted (AVE), factor loadings and Cronbach’s alpha (CA) were evaluated to assess the reliability and validity of the constructs (Fornell & Larcker, 1981). Table 2 indicated the results of CA (ranging from 0.904 to 0.962), CR (ranging from 0.907 to 0.963) and AVE (ranging from 0.621 to 0.733), which meet the threshold criteria. Also, all the factor loadings were above 0.70, which meets the cut-off value of 0.60 (Hu & Bentler, 1999). Furthermore, for discriminant validity, AVE square roots were compared with all the variables inter-correlations, which were greater and hence, confirming discriminant validity ((Fornell & Larcker, 1981).

Table 2.

Assessment of Measurement Model.

Constructs	Items	Factor Loadings	CA	CR	AVE
Information Technology Capabilities	ITC1	0.846	0.948	0.947	0.621
	ITC2	0.737
	ITC3	0.841
	ITC4	0.770
	ITC5	0.765
	ITC6	0.746
	ITC7	0.816
	ITC8	0.715
	ITC9	0.831
	ITC10	0.783
	ITC11	0.807
Innovation Orientation	IO1	0.897	0.942	0.943	0.733
	IO2	0.868
	IO3	0.878
	IO4	0.789
	IO5	0.847
	IO6	0.854
Supply Chain Agility	SCA1	0.838	0.962	0.963	0.682
	SCA2	0.864
	SCA3	0.851
	SCA4	0.778
	SCA5	0.714
	SCA6	0.871
	SCA7	0.780
	SCA8	0.824
	SCA9	0.875
	SCA10	0.842
	SCA11	0.793
	SCA12	0.865
Firm Innovative Performance	FIP1	0.854	0.904	0.907	709
	FIP2	0.889
	FIP3	0.776
	FIP4	0.844

Measurement Model

The measurement model was assessed in AMOS and the results show that the model is a good fit as (χ²/df = 1359.727/486 = 2.75, p = 0.000, CFI = 0.914, SRMR = 0.043 and RMSEA = 0.073), which fulfills the model fitness criteria suggested by Hu and Bentler (1999).

Hypothesis Testing

The correlation results are presented in Table 3, indicating that all the proposed relationships are in the expected directions.

Table 3.

Descriptive Results.

	Mean	SD	1	2	3	4	5	6	7
1. Industry	1.56	0.49	1
2. Employees in organisation	2.55	1.14	−0.151**	1
3. Employees in IT Department	2.86	1.59	–0.145**	0.039	1
4. ITC	4.80	1.41	0.028	−0.036	−0.059	(0.788)
5. IO	4.42	1.41	0.010	−0.019	−0.039	0.265**	(0.856)
6. SCA	4.92	1.53	0.085	0.016	−0.053	0.220**	0.479**	(0.826)	*
7. FIP	4.41	1.40	0.064	−0.084	0.009	0.336**	0.282**	0.252**	(0.842)

Note: **Correlation is significant at the 0.01 level (2-tailed). ITC, Information Technology; IO, Innovation Orientation; SCA, Supply Chain Agility; FIP, Firm Innovative Performance. The values in parentheses represent discriminant Validity.

The PROCESS macro was employed to check the proposed hypotheses recommended by Hayes et al. (2017). The results of direct and indirect relationships are presented in Table 4. IT capabilities have a positive substantial effect on firm innovative performance as β = 0.33** and t = 6.51, confirming H1. The SCA mediates the relationship between IT capabilities and firm innovative performance as both lower and upper confidence intervals are positive (0.0157, 0.0810) and did not include zero, confirming H2.

Table 4.

Process Macro Results.

Outcome: FIP	β	SE	t	P
Constant	2.81	0.26	10.92	0.000
ITC	0.33	0.05	6.51	0.000
Outcome: SCA	β	SE	t
Constant	3.76	0.29	12.93	0.000
ITC	0.24	0.06	4.12	0.000
Outcome: ECI	β	SE	t
Constant	2.16	0.31	6.99	0.000
SCA	0.17	0.04	3.59	0.000
ITC	0.29	0.05	5.67	0.000
	Effect	SE	LL 95% CI	UL 95 % CI
Indirect effect	0.04	0.01	0.0157	0.0810
	Effect	SE	z	p
Normal theory test for indirect effect	0.04	0.02	2.66	0.007

Note: CI, Confident Interval; LL, Lower Limit; UL, Upper Limit; ITC, Information Technology; SCA, Supply Chain Agility; FIP, Firm Innovative Performance.

Table 5 indicates the results of the moderating role of innovation orientation between the relationship of IT capabilities and SCA. The significant relationship (IT capabilities × innovation orientation) value (β = 0.12**, t = 2.56) supports H3. Innovation orientation was divided into low (–1 SD) and high (+1 SD) levels to identify the nature of interaction effects. Figure 2 shows the graphical illustration for moderation effect. IT capabilities and SCA is weaker (β = 0.02, t = 0.27, CI = −0.1642–0.1663) at low levels of innovation orientation, while stronger (β = 0.32**, t = 3.92, CI = 0.1584–0.4771) at high levels of innovation orientation.

Table 5.

Moderation Effect.

Outcome: SCA	β	SE	t	p	LL 95% CI	UL 95 % CI
Constant	4.85	0.08	60.24	0.000	4.6933	5.0102
ITC	0.15	0.06	2.42	0.016	0.0271	0.2635
IO	0.48	0.07	6.93	0.000	0.3438	0.6161
ITC x IO	0.12	0.05	2.56	0.010	0.0286	0.2153

Note: CI, Confident Interval; LU, Lower Limit; UL, Upper Limit; ITC, Information Technology Capabilities; IO, Innovation Orientation; SCA, Supply Chain Agility.

Figure 2.

Note: Between the relationship of information technology capabilities (ITC) and supply chain agility (SCA).

Discussion

In highly competitive and volatile environment, firms are continuously striving to embrace their resources and capabilities into their business strategies resulting in sustainable competitive advantage. Among all other resources, information technology is a physical resource that enables the firm to co-create business value for its ultimate stakeholders (Antoni et al., 2020). Moreover, IT is also entitled as an organisational capability to lead the way by innovating the existing business practises, processes and output as well. The capability–resource association highlighted the urgency and necessity of multifaceted bundle of IT resources of firm to innovate performance (Chang et al., 2015). IT capabilities enable firms to coordinate to mobilise and deploy the right number of resources at right time and right place to achieve the business goals efficiently and effectively. This ‘right’ philosophy is inevitably crucial to improve the firm performance. Researcher used the theoretical lens of ‘Dynamic Capability View (DCV)’ to get novel insights about how IT capabilities, leading to innovative firm performance (Vogel & Güttel, 2013). Firm innovative performance has the propensity to be influenced by IT capabilities and is an important source of competitive advantage for organisations that allow exploration and exploitation of new opportunities. Therefore, it becomes more significant for under-developing countries such as Pakistan, especially for manufacturing and services sectors. The reason is, according to Pakistan Bureau of Statistics (2021), industrial/manufacturing sector contributes 12.44%, and services sector contributes 38.15% to the total GDP of Pakistan; as given in Tables 6–8).

In this context, this study is intended to determine the role of IT capabilities in firm innovative performance through mediation of supply chain agility, while innovation orientation was proposed as moderator to stimulate the link of IT capabilities and supply chain. Our study extended the theoretical foundation presented by Naidoo and Hoque (2018) and Rehman et al. (2019) that IT capability is the magic ingredient to lead the performance endeavours to the most novel end-to-end solutions of the problems enlightened by the ultimate stakeholders. The results exhibit a positive significant link between IT capabilities and firm innovative performance.

Table 6.

Gross Domestic Product (GDP) of Pakistan and Different Sectors Contributions to GDP in 2020–2021.

S. No	Industry/Sector	Year	% of GDP	Data in $US Million	Data in PKR Million
A.	Agriculture, forestry and fishing, value added (% of GDP)	2020	21.863	71,876.56	8,137,860
A.	Agriculture, forestry and fishing, value added (% of GDP)	2021	22.964	74,376.49	8,420,902
B.	Industry(including construction), value added (% of GDP)	2020	18.602	58,853.60	6,403,231
B.	Industry(including construction), value added (% of GDP)	2021	18.703	63,436.14	6,901,808
C.	Services, value added (% of GDP)	2020	53.656	173,084.53	20,024,962
C.	Services, value added (% of GDP)	2021	52.147	182,957.06	21,167,161

Source: Pakistan bureau of statistics https://www.sbp.org.pk/ecodata/GDP_table.xlsx

Table 7.

Contribution of Exports of ICT Goods and Services Towards Total Goods and Services in Pakistan (%).

Year	ICT Service Exports (% of ServiceExports, BoP)	ICT Goods Exports (% of Total Goods Exports)
2010	7	0.2
2011	9	0.2
2012	9	0.2
2013	17	0.2
2014	14	0.2
2015	13	0.2
2016	17	0.3
2017	16	0.2
2018	19	0.2
2019	22	0.1
2020	32	0.1
2021	38	..

Source: WDI, World Bank (2022).

Table 8.

Domestic and International IT Services Firms Operating in Pakistan.

Local IT Firms in Pakistan
Company Name	Services	Workforce 2021	2021	2020	2019	2018	2017
Systems Limited	IT-based services	4271	$10.1M	$33.3M	$20.3M	$16.6M	$10.2M
NETSOL Tech		1300+	$55M	$56M	$68M	$61M	$65M
Folio3		200+	$149M estimated annual revenues
Arpatech		250+	$19.1M estimated annual revenues
TRG Pakistan		20000+	$6.5M	$600.7M	$515.6M	$446.1M	$1000
10 Pearls		1200+	$282.6M	–	–	$237.7B	–
Inbox Business Technologies		1700	$10.2M	$7.9M	$39k	–	–
International IT firms in Pakistan
IBM	IT-based services	10000+	$57.3M	$55.2M	$57.7M	$79.6M	$79.1M
Microsoft		10000+	$198.3M	$168.1M	$143.0M	$125.8M	$110.4M
Cisco		10000+	$51.6M	$49.8M	$49.3M	$51.9M	$49.3M
Siemens		10000+	$74.4M	$64.0M	$98.0M	$98.9M	$91.8M
Oracle		10000+	$42.4M	$40.5M	$39.1M	$39.5M	$39.4M
Nielsen		10000+	$3.5M	$3.4M	$3.4M	$6.5M	$6.6M
Afiniti		2000+	$410M	–	–	$130M	$80M

Source: Firm’s websites.

This study took insights from Geyi et al. (2020) and Irfan et al. (2019) to determine the direct impact of (a) IT capabilities on supply chain agility, (b) supply chain agility and firm innovative performance separately. While, in the milieu of technological revolution, this study proposed the unique contribution of supply chain agility as mediator between IT capabilities and firm innovative performance. The findings postulate that supply chain agility proved as a significant mediator between IT capability and firm innovative performance. Andonova and Losada-Otálora (2020) claimed that innovation orientation is a tool or guiding mechanism to help the firms in devising strategy or defining policies leading towards firm innovative performance. It is a substantial framework to materialise the conceptual thoughts into novel process, product or service accordingly (Colclough et al., 2019; Wang et al., 2020). The findings of this paper supported the notion expressed by Lai et al. (2016) and Andonova and Losada-Otálora (2020) that innovation orientation is the control factor to boost the associational effect of IT capabilities and form innovative performance. The results of the study are further evocative for the entrepreneurial-oriented venture who have the potential to reconfigure and deploy IT capabilities to create novelty in the existing system and process. The motivation to ‘bring something new’ leads the firm towards sustainable competitive advantage. By summing up the whole discussion, it is evident that our three hypotheses (H1 for direct relationship, H2 for indirect relationship and H3 for moderating effect) have been supported and accepted.

Theoretical Implications

The findings of this study presented a sound theoretical contribution about the interlinkage of IT capabilities and firm innovative performance in the presence of supply chain agility as mediating construct. This study enriched the literature with the novel bequest of innovation orientation to stimulate the consequential parameter of IT capabilities of firm in the form of innovative performance. Indeed, this study is an extension of intellectual work of Andonova and Losada-Otálora (2020), Rehman et al. (2019) by introducing the innovation orientation as moderator. This study confirmed that present literature amelioration to clarify the notion that how IT capabilities of firm can lead towards sustainable competitive advantage and what are the control mechanisms for it. So, this study makes the novel and significant contributions by effectuating the gap that exist in literature.

Practical Implications

This study proposed numerous implications for policymakers powered by the vision to boost the organisational productivity level. The findings of this study present the pathway to innovate the firm performance for ultimate sustainable competitive advantage. IT capabilities are claimed to bring the agility in supply chain and ultimate innovative performance. This study recommends the decision makers to invest in human resource development, especially in the development of IT capabilities of their work personnel. Human resource department should hire the IT capable resource persons to handle the rapid transformation of competitive environment, deal with the continuous variation of customer demands accordingly. Furthermore, special incentives or comprehensive compensation programme should be introduced to motivate the team for the continuous renewal and upgradation of product, services or process. Researchers highlighted that firms’ top management should have entrepreneurial-oriented stance to achieve the targeted innovative performance rather than traditional financial performance. Moreover, policy makers are advised to devise simple and flexible innovative strategies to survive in highly competitive market dynamism.

Limitations and Future Research Directions

This study has certain potential limitations that redirected future researchers to explore the unaddressed domains. From methodological perspective, this study is limited to cross-sector research that can be extended to longitudinal to determine the impact of causal relationship at multiple time frames. Furthermore, this study is purely confined to quantitative research design that can be further explored by future researchers to untapped its other antecedents and consequences. Another recommendation is to generalise its findings to other cross-cultural boundaries and contexts. This study is limited to only IT capabilities of firm that can be enhanced to other managerial and emerging firm capabilities as well. Future researchers are recommended to explore the moderating effect of environmental dynamism or top management support that are claimed as major predictors/controlling factors for firm innovative performance.

Conclusion

Innovation is deemed to be a driving force for the sustainable success of the firm in a highly dynamic and volatile market. To safely dive into stiff competition, firms need to be a trendsetter rather than a trend follower in terms of continuous modification and upgradation of processes, practises, system, products or services. In this context, this study is undertaken to determine the impact of IT capabilities on firm innovative performance through mediating role of supply chain agility. Moreover, this study introduced innovation orientation as moderating/controlling factor to boost the associational connectivity of ITC and supply chain agility. The findings of the study proved that our three hypotheses of direct, indirect and moderating effect have been accepted. The empirical results exhibit that firms can outperform with the right bundle of IT capabilities and supply chain agility. Moreover, innovation orientation is evidenced as a strong significant moderator for the positive association of IT capabilities and supply chain agility.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

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