Tour firms and tour operators perform an intermediary function in the tourism value chain, packaging accommodation, transport, and attraction access into coordinated itineraries for inbound, outbound, and domestic travelers. Unlike accommodation, food service, and transport — each tied to a fixed physical asset base — tour operators compete substantially on relational and informational assets: client relationships, destination knowledge, and partnership networks with suppliers.

This structural difference motivates a distinct set of competitiveness criteria from those used in the companion hotel, restaurant, and transport studies. This article presents a structured survey instrument for tour firms and applies a benchmark-normalization, weighted integral-index method to convert survey responses into a single integral competitiveness index per firm, while retaining destination-coverage breadth as a descriptive indicator reported alongside, rather than folded into, the weighted index.

The purpose of this article is fourfold: (1) to present a survey instrument tailored to tour firms, including a segment-based evaluation module distinguishing inbound, outbound, domestic, and mixed operations; (2) to map survey-derived indicators onto four weighted criteria — customer loyalty, innovation, market share, and partnership-network breadth — while treating destination coverage descriptively; (3) to illustrate the method using an eight-firm sample; and (4) to discuss the policy implications of the results, including the divergence between destination-coverage breadth and the weighted competitiveness ranking.

Bull [1] and Page [2] characterize tour operators as intermediaries whose competitive position depends on supplier relationships and distribution-channel control rather than on physical asset ownership, a framing extended by Buhalis [3] to account for the growing role of digital distribution channels in reshaping intermediary competitiveness.

Reichheld and Sasser [4] established the foundational link between customer retention and firm profitability across service industries, a relationship that Yoon and Uysal [5] extend specifically to tourism, finding that destination and operator loyalty predict repeat patronage and positive word-of-mouth referral, the latter being of particular importance for firms that rely on relational rather than physical-asset-based competitive advantage.

Hjalager's [6] review of tourism innovation identifies product, process, and network innovation as distinct categories relevant to intermediary firms. Gulati, Nohria and Zaheer [7] and Pavlovich [8] establish that partnership-network breadth and embeddedness are independently associated with firm performance in network-dependent industries, providing the conceptual basis for including partnership-network breadth as a fourth weighted criterion alongside loyalty, innovation, and market share. Gummesson's [9] relationship-marketing framework further supports treating relational assets as legitimate, measurable competitiveness criteria rather than residual, unmeasured factors.

Sheldon [10] documents the early adoption of information-technology systems by tour operators as a distinct competitive lever beyond relational assets alone, complementing this study's innovation criterion. Medina-Muñoz, Medina-Muñoz and García-Falcón [11] examine tour-operator-supplier relationship quality as a determinant of operator performance, reinforcing the rationale for the partnership-network criterion used in this study. Cetin and Bilgihan [12] link destination experience quality to operator-level loyalty outcomes, while Yale's [13] operational overview of tour-operating business practice informs the questionnaire's product-range and segment-based evaluation sections (Sections 3 and 8).

The survey instrument comprises eight sections administered to tour-firm owners or managers: (1) firm profile — location, year of establishment, staff count; (2) client base — total clients served annually and returning-client count; (3) product range — number of distinct tour products/itineraries offered; (4) destination coverage — number of distinct destinations included across all offered itineraries; (5) innovation — count of new products introduced in the past two years; (6) market position — estimated count of tourism transactions/bookings processed annually as an absolute market-presence indicator; (7) partnership networks — count of formal partnerships with guides, hotels, and transport operators; and (8) segment-based evaluation — separate assessment of performance across inbound, outbound, and domestic segments where the firm is active in more than one.

Five survey-derived indicators are computed: customer loyalty (LOYraw = returning clients / total clients), innovation (INNraw = new products introduced / total products), market share (MSraw, the absolute count of tourism transactions processed, used directly as a market-presence proxy), destination-coverage breadth (DSTraw, the count of distinct destinations covered, retained as a descriptive indicator), and partnership-network breadth (PARraw = count of guide partnerships + hotel partnerships + transport partnerships). Four of these five indicators — LOY, INN, MS, and PAR — are normalized against the sample maximum and weighted; DST is reported descriptively and excluded from the weighted index, as discussed in Section 3.2 below.

Ii,norm = Ii,raw / max_j ( Ij,raw ) ( 1)

and the weighted integral competitiveness index is:

Integral(T) i = w1·LOYi + w2·INNi + w3·MSi + w4·PARi ( 2)

with illustrative weights w = (0.3, 0.2, 0.3, 0.2), giving loyalty and market share somewhat greater weight than innovation and partnership breadth, following the general formulation developed for the BoburCalculator algorithm [14]. Destination-coverage breadth (DST) is excluded from the weighted index because it measures the scope of a firm's product offering rather than its competitive performance within that scope, and because including an unbounded count alongside ratio-based indicators would risk allowing scale alone to dominate the index; it is instead reported descriptively alongside the weighted results in Table 3.

The instrument was administered to eight tour firms (TF1–TF8) across Samarkand, Bukhara, Tashkent, and Khiva, spanning inbound, outbound, domestic, and mixed-segment operations. As with the companion sector studies, the sample is illustrative rather than representative, disclosed to demonstrate the computational mechanics of the method.

TF6, the firm with the sample's broadest destination coverage (33 destinations, descriptively reported), ranks only fourth on the weighted integral index, behind TF5, TF3, and TF1, each of which covers fewer destinations but scores more strongly on loyalty, innovation, market share, and partnership breadth. This divergence illustrates that destination-coverage breadth, while a meaningful descriptive characteristic of a tour firm's product scope, is conceptually and empirically distinct from the weighted competitiveness construct measured by the integral index in this study.

Uzbekistan's improving rank on the Travel & Tourism Development Index, alongside a rising domestic-spending share of total tourism expenditure documented in sector estimates [15], provides macro-level context for firm-level results: as more travel is intermediated through formal tour-operator channels, firm-level competitiveness differentials of the kind measured here carry growing aggregate economic significance.

Three considerations follow from the results. First, the comparatively low weight assigned to innovation (0.2) in the illustrative scheme may understate its forward-looking importance; sector associations could consider a higher innovation weight when using the index to identify firms positioned for future, rather than only current, competitiveness. Second, the deliberate exclusion of destination-coverage breadth from the weighted index reflects a methodological judgment that scope and performance-within-scope are distinct constructs deserving separate reporting rather than conflation into a single number; sector stakeholders evaluating the index should retain this distinction when interpreting rankings. Third, the partnership-network criterion's contribution to top-ranked firms' scores suggests that destination management organizations seeking to raise sector-wide competitiveness might support smaller firms in establishing formal partnerships with guides, hotels, and transport operators, lowering the relational barriers that appear to separate top- and bottom-ranked firms in this sample.

This study presented a structured survey instrument and a benchmark-normalization, weighted integral-index method for assessing tour-firm competitiveness, illustrated using an eight-firm sample spanning inbound, outbound, domestic, and mixed-segment operations across four Uzbek cities. The results show that destination-coverage breadth and the weighted competitiveness construct are empirically distinct, with the broadest-coverage firm ranking only fourth, and that customer loyalty, innovation, market presence, and partnership-network breadth jointly differentiate firms more sharply than coverage scope alone.

The method offers tour-sector associations and individual operators a transparent way to benchmark competitiveness while preserving destination-coverage breadth as a separately reported, descriptive characteristic rather than folding it into a single composite score. Revisiting the innovation weight, supporting partnership-network development among smaller firms, and validating the method with larger, randomized samples represent priority directions for follow-up empirical work.

The author thanks the International University of Tourism and Cultural Heritage “Silk Road” for institutional support during the preparation of this study. No additional acknowledgments apply.

This research received no external funding from any funding agency in the public, commercial, or not-for-profit sectors.

The author declares no conflict of interest.